Awesome PyTorch

Fast image augmentation library.

Image augmentation library in Python for machine learning. http://augmentor.readthedocs.io

An end-to-end PyTorch framework for image and video classification.

A multi-layer convolution LSTM module

Computer vision in Python with less than 10 lines of code

Detectorch - detectron for PyTorch

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

:fire: 2D and 3D Face alignment library build using pytorch adrianbulat.com

Pretrained Pytorch face detection and recognition models ported from davidsandberg/facenet.

Visualization toolkit for neural networks in PyTorch!

Collection of classification models pretrained on the ImageNet-1K.

Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)

Differentiable computer vision library.

Lightly is a computer vision framework for self-supervised learning.

Tensorflow and OpenAI Clarity's Lucid adapted for PyTorch.

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

A medical imaging framework for Pytorch http://medicaltorch.readthedocs.io

MMAction2 is OpenMMLab's next generation action understanding toolbox and benchmark, a part of the OpenMMLab project.

MMDetection is an open source object detection toolbox, a part of the OpenMMLab project.

MMDetection3D is OpenMMLab's next-generation platform for general 3D object detection, a part of the OpenMMLab project.

MMEditing is a image and video editing toolbox, a part of the OpenMMLab project.

MMPose is a pose estimation toolbox and benchmark, a part of the OpenMMLab project.

MMSegmentation is a semantic segmentation toolbox and benchmark, a part of the OpenMMLab project.

A PyTorch implementation of the DeepDream algorithm. Creates dream-like hallucinogenic visuals.

PyTorch module to use OpenFace's nn4.small2.v1.t7 model

Neural style transfer as a class in PyTorch.

Datasets, Transforms and Models specific to Computer Vision.

Fine-tune pretrained Convolutional Neural Networks with PyTorch.

PyTorch for Semantic Segmentation.

Text recognition combo - CRAFT + CRNN.

PyTorch3D is FAIR's library of reusable components for deep learning with 3D data pytorch3d.org

This is a PyTorch version of RoIAlign. This implementation is based on cropandresize and supports both forward and backward on CPU and GPU.

a lightweight and efficient library to deal with 3D rotations.

Submanifold sparse convolutional networks.

A PyTorch-Based Framework for Deep Learning in Computer Vision.

A semantic segmentation framework by pyotrch

An open-source NLP research library, built on PyTorch.

Interpretable Models for NLP using PyTorch.

simple audio I/O for pytorch.

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

Pytorch-Named-Entity-Recognition-with-BERT.

Pytorch implementation of Google AI's 2018 BERT, with simple annotation

End-to-End Speech Processing Toolkit espnet.github.io/espnet

Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

A very simple framework for state-of-the-art Natural Language Processing (NLP)

Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning.

Sentence embeddings (InferSent) and training code for NLI.

The jiant sentence representation learning toolkit.

Language-Agnostic SEntence Representations

A method to generate speech across multiple speakers

A library for Multilingual Unsupervised or Supervised word Embeddings

Neural Modules: a toolkit for conversational AI nvidia.github.io/NeMo

State-of-the-art coreference resolution based on neural nets and spaCy huggingface.co/coref

Neural Machine Translation Framework in PyTorch.

Open-Source Neural Machine Translation in PyTorch http://opennmt.net

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, speaker embedding

A natural language modeling framework based on PyTorch fb.me/pytextdocs

A software suite for Visual Question Answering

Torch text related contents.

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Text utilities and datasets for PyTorch pytorchnlp.readthedocs.io

A framework for sequence-to-sequence (seq2seq) models implemented in PyTorch.

A library of vectorized implementations of core structured prediction algorithms (HMM, Dep Trees, CKY, ..,)

An implementation of WaveNet with fast generation

Pytorch NLP library based on FastAI.

Reformer, the efficient Transformer, in Pytorch

Unsupervised Language Modeling at scale for robust sentiment classification.

PyTorch ASR Implementation.

SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch.

Tacotron: Towards End-to-End Speech Synthesis.

Toolkit for Machine Learning and Text Generation, in PyTorch texar.io

Metrics for model evaluation in pytorch

NLP library designed for flexible research and development

huggingface Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch. huggingface.co/transformers

Translate - a PyTorch Language Library.

Deep learning for Text2Speech

This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization. arxiv.org/abs/1810.04719

Phrase-Based & Neural Unsupervised Machine Translation.

Unofficial PyTorch implementation of Google AI's VoiceFilter system http://swpark.me/voicefilter

A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

An optimizer that trains as fast as Adam and as good as SGD.a

A Toolbox for Adversarial Robustness (attack/defense/training) Research

Adaptive Neural Execution Engine for PyTorch transformers. Provides per-token dynamic layer skipping, profiler-based gating, and KV-cache-safe sparse inference.

Aorun intend to be a Keras with PyTorch as backend.

An Experimental PyTorch Extension(will be deprecated at a later point)

A library for real-time video stream decoding to CUDA memory tensorstream.argus-ai.com

Arnold - DOOM Agent

A PyTorch library for building deep reinforcement learning agents.

Adaptive Experimentation Platform

A simple, flexible, and extensible template for PyTorch. It's beautiful.

A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch

Convert Caffe models to PyTorch.

Gaussian Processes in Pytorch.

High-level utils for PyTorch DL & RL research. It was developed with a focus on reproducibility, fast experimentation and code/ideas reusing. Being able to research/develop something new, rather than write another regular train loop.

Cogitare - A Modern, Fast, and Modular Deep Learning and Machine Learning framework in Python.

PyTorch reimplementation of Interactive Deep Colorization richzhang.github.io/ideepcolor

Convert torch t7 model to pytorch model and source.

CrypTen is a Privacy Preserving Machine Learning framework written using PyTorch that allows researchers and developers to train models using encrypted data. CrypTen currently supports Secure multi-party computation as its encryption mechanism.

cvxpylayers is a Python library for constructing differentiable convex optimization layers in PyTorch

Lightweight framework for fast prototyping and training deep neural networks in medical imaging delira.rtfd.io

Python package built to ease deep learning on graph, on top of existing DL frameworks. http://dgl.ai.

diffdist is a python library for pytorch. It extends the default functionality of torch.autograd and adds support for differentiable communication between processes.

Decoupled Neural Interfaces using Synthetic Gradients for PyTorch.

Distributed Learning by Pair-Wise Averaging.

It contains an op-for-op PyTorch reimplementation of EfficientNet, along with pre-trained models and examples.

ELF: a platform for game research.

A multi-model machine learning feature embedding database http://euclidesdb.readthedocs.io

C++ extensions in PyTorch

The fast.ai deep learning library, lessons, and tutorials

Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses

An ML framework to accelerate research and its path to production. flambe.ai

A unified approach to federated learning, analytics, and evaluation. It allows to federated any machine learning workload.

PyTorch, unlike lua torch, has autograd in it's core, so using modular structure of torch.nn modules is not necessary, one can easily allocate needed Variables and write a function that utilizes them, which is sometimes more convenient. This repo contains model definitions in this functional way, with pretrained weights for some models.

Pytorch-based tools for visualizing and understanding the neurons of a GAN. gandissect.csail.mit.edu

generativezoo is a repository that provides working implementations of some generative models in PyTorch.

Riemannian Adaptive Optimization Methods with pytorch optim

A highly efficient and modular implementation of Gaussian Processes in PyTorch.

GPyTorch is a Gaussian Process library, implemented using PyTorch. It is designed for creating flexible and modular Gaussian Process models with ease, so that you don't have to be an expert to use GPs.

hessian in pytorch.

higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

Pytorch Hub is a pre-trained model repository designed to facilitate research reproducibility.

Ignite is a high-level library to help with training neural networks in PyTorch.

A utility library around PyTorch

A scikit-learn compatible neural network library that wraps pytorch.

Deep reinforcement learning libraries for NVIDIA Jetson TX1/TX2 with PyTorch, OpenAI Gym, and Gazebo robotics simulator.

Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation star2

PyTorch library aimed at accelerating 3D deep learning research

A simple wrapper around pytorch that prevents CUDA out of memory issues.

lagom: A light PyTorch infrastructure to quickly prototype reinforcement learning algorithms.

PyTorch Meta-learning Framework for Researchers http://learn2learn.net

Flash is a collection of tasks for fast prototyping, baselining and fine-tuning scalable Deep Learning models, built on PyTorch Lightning.

Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.

A simple logger for experiments.

learning to search in pytorch

Deep Learning Projects that Build Themselves http://magnet-dl.readthedocs.io/

Write PyTorch code at the level of individual examples, then run it efficiently on minibatches.

A manifold optimization library for deep learning.

Minkowski Engine is an auto-diff library for generalized sparse convolutions and high-dimensional sparse tensors.

Pytorch implementation of MaxPoolingLoss.

Python library for Reinforcement Learning experiments.

Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units paper by trask et.al arxiv.org/pdf/1808.00508.pdf

Parameterized fit and prediction harnesses for pytorch.

A neural assembly compiler for pyTorch based on adaptive-neural-compilation.

Skip bad items in your PyTorch DataLoader, use Transforms as Filters, and more!

OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research mariewelt.github.io/OpenChem

OpenCV implementation of Torchvision's image augmentations

The differentiable OSQP solver layer for PyTorch.

a library for developing deep generative models in a more concise, intuitive and extendable way.

A Keras-like framework for PyTorch that handles much of the boilerplating code needed to train neural networks.

The goal of this repo is to help to reproduce research papers results.

PyTorch based Deep Learning Toolbox

CuPy fused PyTorch neural networks ops

Efficient Spiking Neural Network framework, built on top of PyTorch for GPU acceleration.

Some extra features for pytorch.

A signed and directed extension library for PyTorch Geometric.

A temporal extension library for PyTorch Geometric

convert between pytorch, caffe prototxt/weights and darknet cfg/weights

Compressed Network Search with PyTorch

It contains reviewed implementations of ideas from recent machine learning papers.

PyTorch C++ Reinforcement Learning

PyTorch-CTC is an implementation of CTC (Connectionist Temporal Classification) beam search decoding for PyTorch. C++ code borrowed liberally from TensorFlow with some improvements to increase flexibility.

Code for "Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation" arxiv.org/pdf/1806.08756.pdf

PyTorch docset! use with Dash, Zeal, Velocity, or LovelyDocs.

PyTorch Deep Texture Encoding Network http://hangzh.com/PyTorch-Encoding

This is a CUDA extension for PyTorch which computes the Hadamard product of two tensors.

Super simple fit method for PyTorch modules

Efficient PyTorch Hessian eigendecomposition using the Hessian-vector product and stochastic power iteration.

A PyTorch implementation of L-BFGS.

Rapid research framework for Pytorch. The researcher's version of keras.

Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch.

Convert models from MatConvNet to PyTorch

The easiest way to use metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

Count the FLOPs of your PyTorch model.

Collections of modern optimization algorithms for PyTorch, includes: AccSGD, AdaBound, AdaMod, DiffGrad, Lamb, RAdam, RAdam, Yogi.

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation. StudioGAN aims to offer an identical playground for modern GANs so that machine learning researchers can readily compare and analyze a new idea.

Model summary in PyTorch similar to model.summary() in Keras

PyTorch extensions for fast R&D prototyping and Kaggle farming

This is toolbox project for Pytorch. Aiming to make you write Pytorch code more easier, readable and concise.

Tools for PyTorch

A Collection of Variational Autoencoders (VAE) in PyTorch.

PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs.

Convert PyTorch model to Caffemodel

Convert PyTorch dynamic graph to Keras model.

PyTorch Extension Library of Optimised Graph Cluster Algorithms.

PyTorch wrapper for FFTs

Geometric Deep Learning Extension Library for PyTorch

A small package to create visualizations of PyTorch execution graphs.

A Keras-like framework and utilities for PyTorch

A cleaner way to build neural networks for PyTorch. blue-season.github.io/pywarm

High-level batteries-included neural network training library for Pytorch

Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators.

Neural Network Many-Body Wavefunction Reconstruction

A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io

A differentiable Monte Carlo path tracer

A library for real-world continual learning.

Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods

Reinforcement Learning in PyTorch

Semi-Supervised Learning and Domain Adaptation.

Development branch of the scVI project in PyTorch

Implementations of different VAE-based semi-supervised and generative models in PyTorch.

A simplified implemention of Faster R-CNN with competitive performance.

A scikit-learn compatible neural network library that wraps pytorch

Modular Deep Reinforcement Learning framework in PyTorch.

Train and run Pytorch models on Apache Spark.

Deep recommender models using PyTorch.

Training RNNs as Fast as CNNs (arxiv.org/abs/1709.02755)

This module saves PyTorch tensors in tensorboard format for inspection. Currently supports scalar, image, audio, histogram features in tensorboard.

Debugging, monitoring and visualization for Deep Learning and Reinforcement Learning from Microsoft Research.

A Generic Tensor-Network library that is designed for quantum simulation, base on the pytorch.

This package provides a set of transforms and data structures for sampling from in-memory or out-of-memory data.

A PyTorch library for two-sample tests

Torch7 -> CoreML

Accurate Neural Network Potential on PyTorch aiqm.github.io/torchani

torchbearer: A model training library for researchers using PyTorch.

A PyTorch Platform for Distributed RL

Python wrapper for TorchCraft, a bridge between Torch and StarCraft for AI research.

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

drift detection library

Torchélie is a set of utility functions, layers, losses, models, trainers and other things for PyTorch. torchelie.readthedocs.org

TGM: PyTorch Geometry

A GPipe implementation in PyTorch torchgpipe.readthedocs.io

A high level library on top of(not only) Pytorch

Implements the + operator on PyTorch modules, returning sequences.

A minimal dependency library for layer-by-layer profiling of Pytorch models.

Model analyzer in PyTorch.

A library providing various existing GANs in PyTorch.

Velocity in deep-learning research.

volksdep is an open-source toolbox for deploying and accelerating PyTorch, Onnx and Tensorflow models with TensorRT.

Numerically solving and backpropagating through the wave equation arxiv.org/abs/1904.12831

WebDataset is a PyTorch Dataset (IterableDataset) implementation providing efficient access to datasets stored in POSIX tar archives.

Transfer Learning Library

pytorch implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802v2

3D ResNets for Action Recognition.

The pytorch improved re-implementation of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.

PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch

Implements pytorch code for the Accelerated SGD algorithm.

A pytorch implementation of the MICCAI2019 paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation".

PyTorch implementation of adversarial patch.

Deeper DCGAN with AE stabilization

Code for paper "Adversarial Generator-Encoder Networks" by Dmitry Ulyanov, Andrea Vedaldi and Victor Lempitsky which can be found here

A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.

Combining Neural Networks with Personalized PageRank for Classification on Graphs. ICLR 2019.

Code for the paper "Adversarially Regularized Autoencoders for Generating Discrete Structures" by Zhao, Kim, Zhang, Rush and LeCun.

Code and dataset for ACL2018 paper "Exploiting Document Knowledge for Aspect-level Sentiment Classification"

Associative Compression Networks for Representation Learning.

This is PyTorch implementation of A3C as described in Asynchronous Methods for Deep Reinforcement Learning. Since PyTorch has a easy method to control shared memory within multiprocess, we can easily implement asynchronous method like A3C.

A PyTorch implementation of the Transformer model in "Attention is All You Need".https://github.com/thnkim/OpenFacePytorch

Attention transfer in pytorch, read the paper here.

This is a Pytorch implementation of Watch Your Step: Learning Node Embeddings via Graph Attention. NIPS 2018.

Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction

Implementation of Adversarial Variational Optimization in PyTorch.

This is a Pytorch implementation of

Bilinear attention networks for visual question answering.

This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.

PyTorch implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks.

Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"

The author's officially unofficial PyTorch BigGAN implementation.

Binary Stochastic Neurons in PyTorch.

PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnel (ICLR 2018)

Implementation supporting the ICCV 2017 paper "GANs for Biological Image Synthesis".

vqa, bottom-up-attention, pytorch

U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI.

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening arxiv.org/abs/1903.08297

Pytorch implementation of bytenet from "Neural Machine Translation in Linear Time" paper

Capsule Graph Neural Network. (ICLR 2019).

PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules.

Generate captions for an image using PyTorch.

Canonical Appearance Transformations

A PyTorch Implementation of Categorical DQN from A Distributional Perspective on Reinforcement Learning.

PyTorch implementation of the Character-level Convolutional Networks for Text Classification paper.

A Pytorch Implementation of ClariNet arxiv.org/abs/1807.07281

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch.

(Yang Gao, et al.) A Pytorch Implementation for Compact Bilinear Pooling.

CondenseNet: An Efficient DenseNet using Learned Group Convolutions.

PyTorch Implement of Context Encoders

Reimplementation of Continuous Deep Q-Learning with Model-based Acceleration.

Convolutional 2D Knowledge Graph Embeddings

PyTorch implementation for Convolutional Networks with Adaptive Inference Graphs.

Pytorch implementation of CoordConv introduced in 'An intriguing failing of convolutional neural networks and the CoordConv solution' paper. (arxiv.org/pdf/1807.03247.pdf)

This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper.

Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks.

a pytorch implementation of auto-punctuation learned character by character.

Pytorch implementation of the DeepDream computer vision algorithm.

Wind Speed Prediction using LSTMs in PyTorch (arxiv.org/pdf/1707.08110.pdf)

Deep Learning Head Pose Estimation using PyTorch.

A python implementation of Deep-Image-Analogy based on pytorch.

Image restoration with neural networks but without learning.

LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods.

This repository contains PyTorch implementations of deep reinforcement learning algorithms.

A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation.', ECCV 2016

This repository contains the SystemVerilog RTL, C++, HLS (Intel FPGA OpenCL to wrap RTL code) and Python needed to reproduce the numerical results in "Rethinking floating point for deep learning"

An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch.

This is a PyTorch implementation of the AAAI-18 paper Gated-Attention Architectures for Task-Oriented Language Grounding

Implementation of DeepSpeech2 using Baidu Warp-CTC. Creates a network based on the DeepSpeech2 architecture, trained with the CTC activation function.

PyTorch implementation of convolutional networks-based text-to-speech synthesis models

PyTorch implementation of Deformable Convolution.

PyTorch implementation of CloudWalk's recent paper DenseBody.

This is a PyTorch implementation of the DenseNet-BC architecture as described in the paper Densely Connected Convolutional Networks by G. Huang, Z. Liu, K. Weinberger, and L. van der Maaten. This implementation gets a CIFAR-10+ error rate of 4.77 with a 100-layer DenseNet-BC with a growth rate of 12. Their official implementation and links to many other third-party implementations are available in the liuzhuang13/DenseNet repo on GitHub.

PyTorch DepthNet Training on Still Box dataset.

A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.

Deep Extreme Cut http://www.vision.ee.ethz.ch/~cvlsegmentation/dextr

A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network".

A provable defense against adversarial examples and library for building compatible PyTorch models.

PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

Distance-Encoding - Design Provably More PowerfulGNNs for Structural Representation Learning.

Differentiable Neural Computers, for Pytorch

Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch

PyTorch's version of Doom-net implementing some RL models in ViZDoom environment.

A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.

An implementation of Deep Recursive Residual Network for Super Resolution (DRRN), CVPR 2017

Embed to Control implementation in PyTorch.

Task-based end-to-end model learning.

PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)

A memory-efficient implementation of DenseNets

A PyTorch implementation of EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Official implementation of the ICML'19 paper "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis".

PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing".

Deal or No Deal? End-to-End Learning for Negotiation Dialogues

Pytorch implementation of Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network. This work has won the first place in PIRM2018-SR competition (region 1) held as part of the ECCV 2018.

An implementation of Eve Optimizer, proposed in Imploving Stochastic Gradient Descent with Feedback, Koushik and Hayashi, 2016.

An implementation of Elastic Weight Consolidation (EWC), proposed in James Kirkpatrick et al. Overcoming catastrophic forgetting in neural networks 2016(10.1073/pnas.1611835114).

Pytorch implementation of face attention network as described in Face Attention Network: An Effective Face Detector for the Occluded Faces.

A PyTorch Implementation of FaceBoxes.

Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017

Fast Neural Style for Image Style Transform by Pytorch .

pytorch implementation of fast-neural-style, The model uses the method described in Perceptual Losses for Real-Time Style Transfer and Super-Resolution along with Instance Normalization.

This is a PyTorch implementation of Faster RCNN. This project is mainly based on py-faster-rcnn and TFFRCNN.For details about R-CNN please refer to the paper Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks by Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun.

This project is a faster faster R-CNN implementation, aimed to accelerating the training of faster R-CNN object detection models.

A Closed-form Solution to Photorealistic Image Stylization

trying to be the most easiest and just get-to-use pytorch implementation of FCN (Fully Convolotional Networks)

Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"

Unofficial Implementation of FFTNet vocode paper.

Pytorch implementation of ICLR 2018 paper Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge.

Pytorch implementation of FlowNet by Dosovitskiy et al.

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

FluidNet re-written with ATen tensor lib.

A PyTorch implementation of a Factorization Machine module in cython.

Pytorch implementation of "Forward Thinking: Building and Training Neural Networks One Layer at a Time" https://arxiv.org/pdf/1706.02480.pdf

PyTorch library for custom backward passes, straight-through estimators and gradient transforms.

Accelerate Neural Net Training by Progressively Freezing Layers.

This is a Pytorch implementation of Graph Classification using Structural Attention. KDD 2018.

Code for "On the Effects of Batch and Weight Normalization in Generative Adversarial Networks"

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN.

Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"

A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN).

PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions (arxiv.org/abs/1807.03039)

This implements one of result networks from Large-scale evolution of image classifiers by Esteban Real, et. al.

Simple Text-Generator with OpenAI gpt-2 Pytorch Implementation

Pytorch implementation of Grad-CAM

Continuum Learning with GEM: Gradient Episodic Memory. https://arxiv.org/abs/1706.08840

PyTorch implementation of graph ConvNets, NIPS’16

Simple reference implementation of GraphSAGE.

This is a Pytorch implementation of Graph Wavelet Neural Network. ICLR 2019.

A pytorch reimplementation of { Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation }.

PyTorch reimplementation of Google's TensorFlow CNNs for keyword spotting.

In-Place Activated BatchNorm for Memory-Optimized Training of DNNs

This is the pytorch implementation of the paper - Axiomatic Attribution for Deep Networks.

Pytorch Implementation of Interaction Networks for Learning about Objects, Relations and Physics.

Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

pytorch implementation of Learning to Communicate with Deep Multi-Agent Reinforcement Learning paper.

PyTorch implementation of Learning to learn by gradient descent by gradient descent.

Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning.

Implementations of polygamma, lgamma, and beta functions for PyTorch

Empower Sequence Labeling with Task-Aware Language Model http://arxiv.org/abs/1709.04109

Pytorch implementation of LOLA (arxiv.org/abs/1709.04326) using DiCE (arxiv.org/abs/1802.05098)

loss-landscape Code for visualizing the loss landscape of neural nets.

Official implementation of the NeurIPS2021 paper "MagNet: A Neural Network for Directed Graphs".

Pytorch implementation of MalConv.

A PyTorch implementation of the architecture of Mask RCNN, serves as an introduction to working with PyTorch

Mask RCNN in PyTorch.

Codes for "meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting".

Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"

MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. ICML 2019.

A PyTorch implementation of the paper Mixup: Beyond Empirical Risk Minimization in PyTorch.

PyTorch Implementation of CycleGAN and SGAN for Domain Transfer (Minimal).

Molecular AutoEncoder in PyTorch

Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units arxiv.org/pdf/1808.00508.pdf

Cancer metastasis detection with neural conditional random field (NCRF)

An introduction to PyTorch through the Neural-Style algorithm (https://arxiv.org/abs/1508.06576) developed by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge.

PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.

A PyTorch Implementation of Neural IMage Assessment.

A PyTorch Implementation of Neural IMage Assessment.

A PyTorch implementation of Justin Johnson's Neural-style.

image captioning model in pytorch(finetunable cnn in branch withfinetune)

A Higher-Order Graph Convolutional Layer. NeurIPS 2018.

Neural Module Network for VQA in Pytorch.

Neural Message Passing for Computer Vision

Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin.

Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference".

PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"

A PyTorch Implementation of Improving Semantic Segmentation via Video Propagation and Label Relaxation, In CVPR2019.

A PyTorch Implementation of Unsupervised Video Interpolation Using Cycle Consistency, In ICCV 2019.

A PyTorch implementation of "Joint Discriminative and Generative Learning for Person Re-identification" (CVPR19 Oral).

Principled Detection of Out-of-Distribution Examples in Neural Networks.

Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks".

This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch source code to reproduce the experiments in our paper OptNet: Differentiable Optimization as a Layer in Neural Networks.

A PyTorch implementation of the paper "Oriented Response Networks" in CVPR 2017.

TensorFlow and PyTorch layers for generating Orthogonal Polynomials.

Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning arxiv.org/abs/1711.05769

Pathfinder Discovery Networks for Neural Message Passing.

PyTorch for Person re-ID.

Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation

Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights arxiv.org/abs/1801.06519

Pixel-wise segmentation on VOC2012 dataset using pytorch.

PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".

Synthesizing and manipulating 2048x1024 images with conditional GANs tcwang0509.github.io/pix2pixHD

PyTorch implementation of PNASNet-5 on ImageNet.

PyTorch implementation of CVPR'18 - Perturbative Neural Networks http://xujuefei.com/pnn.html.

PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations".

pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

Implements an infinite sum of poisson-weighted convolutions

This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch.

PyTorch inference for "Progressive Growing of GANs" with CelebA snapshot.

Implementation of Prototypical Networks for Few Shot Learning (arxiv.org/abs/1703.05175) in Pytorch

Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps.

imlementation of the the Pointer Sentinel Mixture Model, as described in the paper by Stephen Merity et al.

PyTorch implementation of PSPNet segmentation network

Dilated RNNs in pytorch.

Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

Graph Convolutional Networks in PyTorch.

A Python library for learning and evaluating knowledge graph embeddings.

A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, arxiv.org/abs/1610.02915)

Fast Scattering Transform with CuPy/PyTorch,read the paper here

A Port of Fréchet Inception Distance (FID score) to PyTorch

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO) and Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR).

Pytorch implementation of Hinton's Dynamic Routing Between Capsules.

Compressed Video Action Recognition

PyTorch implementation for both unpaired and paired image-to-image translation.

pytorch-deeplab-resnet-model.

PyTorch implementation of Deformable Convolution.

Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom.

Pytorch implementation of Distributed Proximal Policy Optimization: arxiv.org/abs/1707.02286

Deep Q-Learning Network in pytorch.

This is a PyTorch implementation of Evolution Strategies .

PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation

A pytorch implementation of faster RCNN detection framework based on Xinlei Chen's tf-faster-rcnn.

PyTorch implementation of Fully Convolutional Networks.

PyTorch implementations of algorithms for density estimation

PyTorch implementations of Generative Adversarial Networks.

Collection of generative models in Pytorch version.

Pytorch implementation of i-RevNets.

MADE (Masked Autoencoder Density Estimation) implementation in PyTorch

PyTorch implementation of MAML: arxiv.org/abs/1703.03400

The Noise Contrastive Estimation for softmax output written in Pytorch

PyTorch Implementation of Neural Episodic Control (NEC)

Pytorch implementation of DeepMind's differentiable neural computer paper.

pytorch ntm implementation.

This is a PyTorch implementation of the TensorFlow code provided with OpenAI's paper "Improving Language Understanding by Generative Pre-Training" by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever.

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet).

A PyTorch toolkit for 2D Human Pose Estimation.

PyTorch Implementation of Realtime Multi-Person Pose Estimation project.

PyTorch implementation for 3D human pose estimation

PyTorch version of Google AI's BERT model with script to load Google's pre-trained models

PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.

Pruning neural networks: is it time to nip it in the bud?

PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference

PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM

RetinaNet in PyTorch

Transfer Learning Shootout for PyTorch's model zoo (torchvision)

Deep Reinforcement Learning with pytorch & visdom

Intent parsing and slot filling in PyTorch with seq2seq + attention

Skipgram Negative Sampling in PyTorch.

PyTorch implementation of SIFT descriptor.

a pytorch implementation of arxiv.org/abs/1704.03477

SmoothGrad implementation in PyTorch

PyTorch Implementation of Multi-style Generative Network for Real-time Transfer

pytorch implementation of Attention is all you need.

PyTorch Implementation of Trust Region Policy Optimization (TRPO)

This is a PyTorch implementation of "Trust Region Policy Optimization (TRPO)" with exact Hessian-vector product instead of finite differences approximation.

PyTorch implementation of the Value Iteration Networks (NIPS '16) paper

Pytorch implementation of Value Iteration Networks (NIPS 2016 best paper)

pytorch-yolo2

PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning

This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch.

PyTorch Language Model for Google Billion Word Dataset.

Highway network implemented in pytorch.

Highway networks implemented in PyTorch.

Implementation of the HMAX model of vision in PyTorch.

Minimal But Practical Image Classifier Pipline Using Pytorch, Finetune on ResNet18, Got 99% Accuracy on Own Small Datasets.

An implementation of the Noise Contrastive Estimation algorithm for pyTorch. Working, yet not very efficient.

NEG loss implemented in pytorch.

Implementation of Neural Style Transfer in Pytorch.

Recurrent Variational Autoencoder that generates sequential data implemented in pytorch.

Time Delayed NN implemented in pytorch.

PyTorch implementation of the wavelet analysis found in Torrence and Compo (1998)

an implementation of QANet with PyTorch (EM/F1 = 70.5/77.2 after 20 epoches for about 20 hours on one 1080Ti card.)

A fast and differentiable QP solver for PyTorch. Crafted by Brandon Amos and J. Zico Kolter.

Quantile Regression DQN a Minimal Working Example

PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition"

A PyTorch implementation of Radio Transformer Networks from the paper "An Introduction to Deep Learning for the Physical Layer". arxiv.org/abs/1702.00832

Rainbow: Combining Improvements in Deep Reinforcement Learning

This code has the source code for the paper "Random Erasing Data Augmentation".

Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition".

This is a pytorch version of RealtimeMulti-PersonPoseEstimation, origin code is here .

Pytorch implementation of "A simple neural network module for relational reasoning" (Relational Networks) https://arxiv.org/pdf/1706.01427.pdf

An implementation of DeepMind's Relational Recurrent Neural Networks in PyTorch.

PyTorch Implementation of ReSeg (arxiv.org/pdf/1511.07053.pdf)

Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch.

An implementation of RetinaNet in PyTorch.

Reinforcement learning with implementation of A3C LSTM for Atari 2600.

PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model.

Scaling The Scattering Transform : Deep Hybrid Networks.

Implementation of "Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks", published in CVPR 2018.

Semi-Supervised Graph Classification: A Hierarchical Graph Perspective. (WWW 2019).

Unsupervised Scene Adaptation with Memory Regularization in vivo, In IJCAI 2020.

Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning.

Latest in the field of neural information retrieval / semantic search.

Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch

Sequence-to-Sequence learning using PyTorch

A PyTorch Implementation of Single Shot Scale-invariant Face Detector.

Pytorch version of SfmLearner from Tinghui Zhou et al.

This is a Pytorch implementation of Signed Graph Convolutional Network. ICDM 2018.

An implementation of shampoo.

This is a Pytorch implementation of faceplusplus's ShuffleNet-v2.

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation.

A pytorch implementation of the ACL2019 paper "Simple and Effective Text Matching with Richer Alignment Features".

This is a Pytorch implementation of SINE: Scalable Incomplete Network Embedding. ICDM 2018.

A PyTorch Implementation of Single Shot MultiBox Detector.

A complete pytorch implementation of skipgram model (with subsampling and negative sampling). The embedding result is tested with Spearman's rank correlation.

An experimental technique for efficiently exploring neural architectures.

A PyTorch Implementation of SphereFace.

Splitter: Learning Node Representations that Capture Multiple Social Contexts. (WWW 2019).

Implementation of Squeezenet in pytorch, #### pretrained models on CIFAR10 data to come Plan to train the model on cifar 10 and add block connections too.

SRDenseNet-pytorch（ICCV2017）

Official implementation of the SDM2022 paper "SSSNET: Semi-Supervised Signed Network Clustering".

Pytorch implementation for reproducing StackGANv2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks by Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, Dimitris Metaxas.

A PyTorch implementation of differentiable stacks for use in neural networks.

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Tranlsation.

STEAL - Learning Semantic Boundaries from Noisy Annotations nv-tlabs.github.io/STEAL

Implementation for the paper A Structured Self-Attentive Sentence Embedding, which is published in ICLR 2017: arxiv.org/abs/1703.03130 .

A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks.

Text-to-Face generation using Deep Learning. This project combines two of the recent architectures StackGAN and ProGAN for synthesizing faces from textual descriptions.

Tacotron 2 - PyTorch implementation with faster-than-realtime inference.

PyTorch implementation of Tacotron speech synthesis model.

PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning" arxiv.org/abs/1803.05268

Sequence modeling benchmarks and temporal convolutional networks locuslab/TCN

A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.

A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis.

A Fast Sequence Transducer Implementation with PyTorch Bindings.

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contexthttps://github.com/kimiyoung/transformer-xl

Code for Emergent Translation in Multi-Agent Communication.

Tree LSTM implementation in PyTorch.

Trellis Networks for Sequence Modeling

Temporal Segment Networks (TSN) in PyTorch.

TuckER: Tensor Factorization for Knowledge Graph Completion.

PyTorch Implementation of our Coupled VAE-GAN algorithm for Unsupervised Image-to-Image Translation

Universal Adversarial Triggers for Attacking and Analyzing NLP (EMNLP 2019)

Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling https://jmtomczak.github.io/deebmed.html

Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.

PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.

Implementation of Visual Feature Attribution using Wasserstein GANs (arxiv.org/abs/1711.08998) in PyTorch.

This's an implementation of deepmind Visual Interaction Networks paper using pytorch

A Pytorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation.

Pytorch Implementation of winner from VQA Chllange Workshop in CVPR'17.

Visual Question Answering in Pytorch

Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data.

Code for the paper "VSE++: Improved Visual Semantic Embeddings"

wassersteinGAN in pytorch.

A Flow-based Generative Network for Speech Synthesis.

A pytorch implementation of Paper "Improved Training of Wasserstein GANs".

WideResNets for CIFAR10/100 implemented in PyTorch. This implementation requires less GPU memory than what is required by the official Torch implementation: https://github.com/szagoruyko/wide-residual-networks .

PyTorch original implementation of Cross-lingual Language Model Pretraining.

auto-tuning momentum SGD optimizer

YOLOv2 in PyTorch.

The YOLOv2 is one of the most popular one-stage object detector. This project adopts PyTorch as the developing framework to increase productivity, and utilize ONNX to convert models into Caffe 2 to benifit engineering deployment.

YOLOv3: Training and inference in PyTorch pjreddie.com/darknet/yolo

Various experiments on the Fashion-MNIST dataset from Zalando.

GPU-accelerated PyTorch implementation of "Zero-shot User Intent Detection via Capsule Neural Networks".

Bayesian optimization in PyTorch

A library for running membership inference attacks against ML models.

Unsupervised learning and generative models in python/pytorch.

Probabilistic Torch is library for deep generative models that extends PyTorch.

ProGAN package implemented as an extension of PyTorch nn.Module.

Probabilistic Programming and Statistical Inference in PyTorch

A PyTorch-based library for probabilistic programming and inference compilation.

Deep universal probabilistic programming with Python and PyTorch http://pyro.ai

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch.

Model interpretability and understanding for PyTorch.

Tensors and Dynamic neural networks in Python with strong GPU acceleration.

An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks. kaggle competition.

A list of awesome PyTorch scholarship articles, guides, blogs, courses and other resources.

Compare outputs between layers written in Tensorflow and layers written in Pytorch.

Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch.

A practical guide to build neural network models in text and vision using PyTorch. Purchase on Amazon github code repo

A nonprofit community run, 5-day Deep Learning Bootcamp http://deep-ml.com.

Pytorch implementation of deep person re-identification approaches.

Self Driving RC Car Code.

"Don't code your UI, Draw it !"

Draw like Bob Ross using the power of Neural Networks (With PyTorch)!

Example repository for custom C++/CUDA operators for TorchScript.

Collection of generative models, e.g. GAN, VAE in Tensorflow, Keras, and Pytorch. http://wiseodd.github.io

Tensors and neural networks in Haskell

Malmo Collaborative AI Challenge - Team Pig Catcher

A raytracer written in PyTorch (raynet?)

All-in-one web IDE for machine learning and data science. Combines Jupyter, VS Code, PyTorch, and many other tools/libraries into one Docker image.

PyTorch - Python + Nim

OCaml bindings for PyTorch.

.

A project similar to Jupyter Notebook Scientific Python Stack

Style guide for PyTorch code. Consistent and good code style helps collaboration and prevents errors!

an informative thread on reddit.

Implement A3C for Mujoco gym envs.

Serving PyTorch 1.0 Models as a Web Server in C++.

Repo for Object Detection, Segmentation & Pose Estimation.

PyTorch 1.0 inference in C++ on Windows10 platforms.

Kaggle 9th place single model solution for TGS Salt Identification Challenge.

A few Windows specific scripts for PyTorch.

PyTorch template project

Totally Versatile Miscellanea for Pytorch

A Marvelous ChatBot implemented using PyTorch.

Code snippets created for the PyTorch discussion board.

A model that takes an image and generates Processing source code to regenerate that image

Rust bindings for PyTorch.

: The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.

.NET bindings for the Pytorch engine

First PyTorch developer conference at 2018.

Adversarial Autoencoders (with Pytorch).

Accelerated Deep Learning with PyTorch at Jupyter Day Atlanta II.

Pytorch easy-to-follow Capsule Network tutorial.

Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition. Currently #27 (0.05074) on the leaderboard.

Pytorch implementation for multiple CNN architectures and improve methods with state-of-the-art results.

This is code of book "Learn Deep Learning with PyTorch" item.jd.com/17915495606.html

This is a complete training example for Deep Convolutional Networks on various datasets (ImageNet, Cifar10, Cifar100, MNIST).

This is an attempt to modify Dive into Deep Learning, Berkeley STAT 157 (Spring 2019) textbook's code into PyTorch.

Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch, the book includes a case study: building an algorithm capable of detecting malignant lung tumors using CT scans.

Interactive and coding-focused tutorial series on introduction to Deep Learning with PyTorch (video).

PyTorch Implementations of Coursera's Deep Learning(deeplearning.ai) Specialization.

An IPython Notebook tutorial on deep learning, with an emphasis on Natural Language Processing.

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning)

The Hitchiker's Guide to PyTorch

A free course by Udacity and facebook, with a good intro to PyTorch, and an interview with Soumith Chintala, one of the original authors of PyTorch.

Kind PyTorch Tutorial for beginners.

A collection of PyTorch implementations of neural networks architectures and algorithms with side-by-side notes.

Various tutorials given for welcoming new students at MILA.

Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch

This is an example of how to train a MNIST network in Python and run it in c++ with pytorch 1.0

MRI analysis using PyTorch and MedicalTorch

Singing Voice Separation via Recurrent Inference and Skip-Filtering Connections - PyTorch Implementation. Demo: js-mim.github.io/msspytorch

PyTorch solution of named entity recognition task Using Google AI's pre-trained BERT model.

torch code to decode (and almost encode) latents from art-DCGAN's Portrait GAN.

: Tutorials explaining different RNN models

This repository aims to help former Torchies more seamlessly transition to the "Containerless" world of PyTorch by providing a list of PyTorch implementations of Torch Table Layers.

A repository showcasing examples of using pytorch

Minimal tutorials for PyTorch adapted from Alec Radford's Theano tutorials.

Some example scripts on pytorch.

A simple implementation of CNN based text classification in Pytorch

PyTorch Tutorials in Chinese.

Various pytorch tutorials.

A unified framework for the image classification task on CIFAR-10/100 and ImageNet.

C++ implementations of PyTorch tutorials for deep learning researchers (based on the Python tutorials from pytorch-tutorial).

Some custom dataset examples for PyTorch

Minicourse in Deep Learning with PyTorch.

pytorch-exercises collection.

simple generative adversarial network (GAN) using PyTorch.

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more.

A couple of scripts to illustrate how to do CNNs and RNNs in PyTorch

a char-RNN based on pytorch.

PyTorch implementation of REINFORCE, This repo supports both continuous and discrete environments in OpenAI gym.

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

How to use Cross Replica / Synchronized Batchnorm in Pytorch.

: Build your neural network easy and fast https://morvanzhou.github.io/tutorials/

tutorial for researchers to learn deep learning with pytorch.

for learning reinforcement learning using PyTorch.

time-series prediction related examples.

pytorch-exercises

A short tutorial on performing fine tuning or transfer learning in PyTorch.

Random tutorials created in NumPy and PyTorch.

Quick PyTorch introduction and tutorial. Targets computer vision, graphics and machine learning researchers eager to try a new framework.

Pytorch easy-to-follow step-by-step Deep Q Learning tutorial with clean readable code.

PyTorch4 tutorial of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay

This example demonstrates how an already existing centralized PyTorch machine learning project can be federated with Flower. A Cifar-10 dataset is used together with a convolutional neural network (CNN).

Sentiment analysis neural network trained by fine tuning BERT on the Stanford Sentiment Treebank, thanks to Hugging Face's Transformers library.

Serverless Machine Learning in Action is a guide to bringing your experimental PyTorch machine learning code to production using serverless capabilities from major cloud providers like AWS, Azure, or GCP.

An implementation of Skip-Thought Vectors in PyTorch.

t-SNE experiments in pytorch

Tensor methods in Python with TensorLy tensorly.github.io/dev

A free FreeCodeCamp book teaching the math behind AI in plain English from an engineering point of view. It covers linear algebra, calculus, probability & statistics, and optimization theory with analogies, real-life applications, and Python code examples.

Thinking in tensors, writing in PyTorch (a hands-on deep learning intro).

Tutorials and examples include Reinforcement Training, NLP, CV

nyu-cv-fall-2017 example

pytorch code for video captioning.