PyTorch超级资源列表(Github 2.4K星)包罗万象

PyTorch超级资源列表(Github 2.4K星)包罗万象 -v7.x

深度学习原理与实践(开源图书)-总目录,建议收藏，告别碎片阅读!

发现了一份极棒的 PyTorch 资源列表，该列表包含了与 PyTorch 相关的众多库、教程与示例、论文实现以及其他资源。实践派赶紧收藏，以备不时之需。由于是资源列表，仅翻译了一级标题，看官见谅。

项目地址：https://github.com/bharathgs/Awesome-pytorch-list

1 Pytorch官方工程

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

2 自然语言处理和语音处理(NLP & Speech Processing):

该部分项目涉及语音识别、多说话人语音处理、机器翻译、共指消解、情感分类、词嵌入/表征、语音生成、文本语音转换、视觉问答等任务，其中有一些是具体论文的 PyTorch 复现，此外还包括一些任务更广泛的库、工具集、框架。

1. pytorch text : Torch text related contents.
2. pytorch-seq2seq: A framework for sequence-to-sequence (seq2seq) models implemented in PyTorch.
3. anuvada: Interpretable Models for NLP using PyTorch.
4. audio: simple audio I/O for pytorch.
5. loop: A method to generate speech across multiple speakers
6. fairseq-py: Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
7. speech: PyTorch ASR Implementation.
8. OpenNMT-py: Open-Source Neural Machine Translation in PyTorch http://opennmt.net
9. neuralcoref: State-of-the-art coreference resolution based on neural nets and spaCy huggingface.co/coref
10. sentiment-discovery: Unsupervised Language Modeling at scale for robust sentiment classification.
11. MUSE: A library for Multilingual Unsupervised or Supervised word Embeddings
12. nmtpytorch: Neural Machine Translation Framework in PyTorch.
13. pytorch-wavenet: An implementation of WaveNet with fast generation
14. Tacotron-pytorch: Tacotron: Towards End-to-End Speech Synthesis.
15. AllenNLP: An open-source NLP research library, built on PyTorch.
16. PyTorch-NLP: Text utilities and datasets for PyTorch pytorchnlp.readthedocs.io
17. quick-nlp: Pytorch NLP library based on FastAI.
18. TTS: Deep learning for Text2Speech
19. LASER: Language-Agnostic SEntence Representations
20. pyannote-audio: Neural building blocks for speaker diarization: speech activity detection, speaker change detection, speaker embedding
21. gensen: Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning.
22. translate: Translate - a PyTorch Language Library.
23. espnet: End-to-End Speech Processing Toolkit espnet.github.io/espnet
24. pythia: A software suite for Visual Question Answering
25. UnsupervisedMT: Phrase-Based & Neural Unsupervised Machine Translation.
26. jiant: The jiant sentence representation learning toolkit.

3 计算机视觉

该部分项目涉及神经风格迁移、图像分类、人脸对齐、语义分割、RoI 计算、图像增强等任务，还有一些特殊的 CNN 架构，以及一些预训练模型的集合。

1. pytorch vision : Datasets, Transforms and Models specific to Computer Vision.
2. pt-styletransfer: Neural style transfer as a class in PyTorch.
3. OpenFacePytorch: PyTorch module to use OpenFace’s nn4.small2.v1.t7 model
4. img_classification_pk_pytorch: Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, …)
5. SparseConvNet: Submanifold sparse convolutional networks.
6. Convolution_LSTM_pytorch: A multi-layer convolution LSTM module
7. face-alignment: ? 2D and 3D Face alignment library build using pytorch adrianbulat.com
8. pytorch-semantic-segmentation: PyTorch for Semantic Segmentation.
9. RoIAlign.pytorch: This is a PyTorch version of RoIAlign. This implementation is based on crop_and_resize and supports both forward and backward on CPU and GPU.
10. pytorch-cnn-finetune: Fine-tune pretrained Convolutional Neural Networks with PyTorch.
11. detectorch: Detectorch - detectron for PyTorch
12. Augmentor: Image augmentation library in Python for machine learning. http://augmentor.readthedocs.io
13. s2cnn:
    This library contains a PyTorch implementation of the SO(3) equivariant CNNs for spherical signals (e.g. omnidirectional cameras, signals on the globe) s

4 概率/生成库(Probabilistic/Generative Libraries):

该部分项目主要涉及概率编程、统计推理和生成模型。

1. ptstat: Probabilistic Programming and Statistical Inference in PyTorch
2. pyro: Deep universal probabilistic programming with Python and PyTorch http://pyro.ai
3. probtorch: Probabilistic Torch is library for deep generative models that extends PyTorch.
4. paysage: Unsupervised learning and generative models in python/pytorch.
5. pyvarinf: Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch.
6. pyprob: A PyTorch-based library for probabilistic programming and inference compilation.
7. mia: A library for running membership inference attacks against ML models.

5 其他库(Other libraries):

1. pytorch extras : Some extra features for pytorch.
2. functional zoo : 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.
3. torch-sampling : This package provides a set of transforms and data structures for sampling from in-memory or out-of-memory data.
4. torchcraft-py : Python wrapper for TorchCraft, a bridge between Torch and StarCraft for AI research.
5. aorun : Aorun intend to be a Keras with PyTorch as backend.
6. logger : A simple logger for experiments.
7. PyTorch-docset : PyTorch docset! use with Dash, Zeal, Velocity, or LovelyDocs.
8. convert_torch_to_pytorch : Convert torch t7 model to pytorch model and source.
9. pretrained-models.pytorch: The goal of this repo is to help to reproduce research papers results.
10. pytorch_fft : PyTorch wrapper for FFTs
11. caffe_to_torch_to_pytorch
12. pytorch-extension: This is a CUDA extension for PyTorch which computes the Hadamard product of two tensors.
13. tensorboard-pytorch: This module saves PyTorch tensors in tensorboard format for inspection. Currently supports scalar, image, audio, histogram features in tensorboard.
14. gpytorch: 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.
15. spotlight: Deep recommender models using PyTorch.
16. pytorch-cns: Compressed Network Search with PyTorch
17. pyinn: CuPy fused PyTorch neural networks ops
18. inferno: A utility library around PyTorch
19. pytorch-fitmodule: Super simple fit method for PyTorch modules
20. inferno-sklearn: A scikit-learn compatible neural network library that wraps pytorch.
21. pytorch-caffe-darknet-convert: convert between pytorch, caffe prototxt/weights and darknet cfg/weights
22. pytorch2caffe: Convert PyTorch model to Caffemodel
23. pytorch-tools: Tools for PyTorch
24. sru: Training RNNs as Fast as CNNs (arxiv.org/abs/1709.02755)
25. torch2coreml: Torch7 -> CoreML
26. PyTorch-Encoding: PyTorch Deep Texture Encoding Network http://hangzh.com/PyTorch-Encoding
27. pytorch-ctc: 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.
28. candlegp: Gaussian Processes in Pytorch.
29. dpwa: Distributed Learning by Pair-Wise Averaging.
30. dni-pytorch: Decoupled Neural Interfaces using Synthetic Gradients for PyTorch.
31. skorch: A scikit-learn compatible neural network library that wraps pytorch
32. ignite: Ignite is a high-level library to help with training neural networks in PyTorch.
33. Arnold: Arnold - DOOM Agent
34. pytorch-mcn: Convert models from MatConvNet to PyTorch
35. simple-faster-rcnn-pytorch: A simplified implemention of Faster R-CNN with competitive performance.
36. generative_zoo: generative_zoo is a repository that provides working implementations of some generative models in PyTorch.
37. pytorchviz: A small package to create visualizations of PyTorch execution graphs.
38. cogitare: Cogitare - A Modern, Fast, and Modular Deep Learning and Machine Learning framework in Python.
39. pydlt: PyTorch based Deep Learning Toolbox
40. semi-supervised-pytorch: Implementations of different VAE-based semi-supervised and generative models in PyTorch.
41. pytorch_cluster: PyTorch Extension Library of Optimised Graph Cluster Algorithms.
42. neural-assembly-compiler: A neural assembly compiler for pyTorch based on adaptive-neural-compilation.
43. caffemodel2pytorch: Convert Caffe models to PyTorch.
44. extension-cpp: C++ extensions in PyTorch
45. pytoune: A Keras-like framework and utilities for PyTorch
46. jetson-reinforcement: Deep reinforcement learning libraries for NVIDIA Jetson TX1/TX2 with PyTorch, OpenAI Gym, and Gazebo robotics simulator.
47. matchbox: Write PyTorch code at the level of individual examples, then run it efficiently on minibatches.
48. torch-two-sample: A PyTorch library for two-sample tests
49. pytorch-summary: Model summary in PyTorch similar to model.summary() in Keras
50. mpl.pytorch: Pytorch implementation of MaxPoolingLoss.
51. scVI-dev: Development branch of the scVI project in PyTorch
52. apex: An Experimental PyTorch Extension(will be deprecated at a later point)
53. ELF: ELF: a platform for game research.
54. Torchlite: A high level library on top of(not only) Pytorch
55. joint-vae: Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation star2
56. SLM-Lab: Modular Deep Reinforcement Learning framework in PyTorch.
57. bindsnet: A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch
58. pro_gan_pytorch: ProGAN package implemented as an extension of PyTorch nn.Module
59. pytorch_geometric: Geometric Deep Learning Extension Library for PyTorch
60. torchplus: Implements the + operator on PyTorch modules, returning sequences.
61. lagom: lagom: A light PyTorch infrastructure to quickly prototype reinforcement learning algorithms.
62. torchbearer: torchbearer: A model training library for researchers using PyTorch.
63. pytorch-maml-rl: Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch.
64. NALU: Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units paper by trask et.al arxiv.org/pdf/1808.00508.pdf
65. QuCumber: Neural Network Many-Body Wavefunction Reconstruction
66. magnet: Deep Learning Projects that Build Themselves http://magnet-dl.readthedocs.io/
67. opencv_transforms: OpenCV implementation of Torchvision’s image augmentations
68. fastai: The fast.ai deep learning library, lessons, and tutorials
69. pytorch-dense-correspondence: Code for “Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation” arxiv.org/pdf/1806.08756.pdf
70. colorization-pytorch: PyTorch reimplementation of Interactive Deep Colorization richzhang.github.io/ideepcolor
71. beauty-net: A simple, flexible, and extensible template for PyTorch. It’s beautiful.
72. OpenChem: OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research mariewelt.github.io/OpenChem
73. torchani: Accurate Neural Network Potential on PyTorch aiqm.github.io/torchani
74. PyTorch-LBFGS: A PyTorch implementation of L-BFGS.
75. gpytorch: A highly efficient and modular implementation of Gaussian Processes in PyTorch.
76. hessian: hessian in pytorch.
77. vel: Velocity in deep-learning research.
78. nonechucks: Skip bad items in your PyTorch DataLoader, use Transforms as Filters, and more!

6 教程与示例(Tutorials & examples)

这一部分包含了很多 PyTorch 教程，它不仅有官方教程与示例，同时还包含很多开发者在学习过程的经验与理解。

1. Practical Pytorch : Tutorials explaining different RNN models
2. DeepLearningForNLPInPytorch : An IPython Notebook tutorial on deep learning, with an emphasis on Natural Language Processing.
3. pytorch-tutorial : tutorial for researchers to learn deep learning with pytorch.
4. pytorch-exercises : pytorch-exercises collection.
5. pytorch tutorials : Various pytorch tutorials.
6. pytorch examples : A repository showcasing examples of using pytorch
7. pytorch practice : Some example scripts on pytorch.
8. pytorch mini tutorials : Minimal tutorials for PyTorch adapted from Alec Radford’s Theano tutorials.
9. pytorch text classification : A simple implementation of CNN based text classification in Pytorch
10. cats vs dogs : Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition. Currently #27 (0.05074) on the leaderboard.
11. convnet : This is a complete training example for Deep Convolutional Networks on various datasets (ImageNet, Cifar10, Cifar100, MNIST).
12. pytorch-generative-adversarial-networks : simple generative adversarial network (GAN) using PyTorch.
13. pytorch containers : 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.
14. T-SNE in pytorch : t-SNE experiments in pytorch
15. AAE_pytorch : Adversarial Autoencoders (with Pytorch).
16. Kind_PyTorch_Tutorial: Kind PyTorch Tutorial for beginners.
17. pytorch-poetry-gen: a char-RNN based on pytorch.
18. pytorch-REINFORCE: PyTorch implementation of REINFORCE, This repo supports both continuous and discrete environments in OpenAI gym.
19. PyTorch-Tutorial: Build your neural network easy and fast https://morvanzhou.github.io/tutorials/
20. pytorch-intro: A couple of scripts to illustrate how to do CNNs and RNNs in PyTorch
21. pytorch-classification: A unified framework for the image classification task on CIFAR-10/100 and ImageNet.
22. pytorch_notebooks - hardmaru: Random tutorials created in NumPy and PyTorch.
23. pytorch_tutoria-quick: Quick PyTorch introduction and tutorial. Targets computer vision, graphics and machine learning researchers eager to try a new framework.
24. Pytorch_fine_tuning_Tutorial: A short tutorial on performing fine tuning or transfer learning in PyTorch.
25. pytorch_exercises: pytorch-exercises
26. traffic-sign-detection: nyu-cv-fall-2017 example
27. mss_pytorch: Singing Voice Separation via Recurrent Inference and Skip-Filtering Connections - PyTorch Implementation. Demo: js-mim.github.io/mss_pytorch
28. DeepNLP-models-Pytorch Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning)
29. Mila introductory tutorials: Various tutorials given for welcoming new students at MILA.
30. pytorch.rl.learning: for learning reinforcement learning using PyTorch.
31. minimal-seq2seq: Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch
32. tensorly-notebooks: Tensor methods in Python with TensorLy tensorly.github.io/dev
33. pytorch_bits: time-series prediction related examples.
34. skip-thoughts: An implementation of Skip-Thought Vectors in PyTorch.
35. video-caption-pytorch: pytorch code for video captioning.
36. Capsule-Network-Tutorial: Pytorch easy-to-follow Capsule Network tutorial.
37. code-of-learn-deep-learning-with-pytorch: This is code of book “Learn Deep Learning with PyTorch” item.jd.com/17915495606.html
38. RL-Adventure: Pytorch easy-to-follow step-by-step Deep Q Learning tutorial with clean readable code.
39. accelerated_dl_pytorch: Accelerated Deep Learning with PyTorch at Jupyter Day Atlanta II.
40. RL-Adventure-2: PyTorch4 tutorial of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
41. Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch)
42. adversarial-autoencoders-with-pytorch
43. transfer learning using pytorch
44. how-to-implement-a-yolo-object-detector-in-pytorch
45. pytorch-for-recommenders-101
46. pytorch-for-numpy-users
47. PyTorch Tutorial: PyTorch Tutorials in Chinese.
48. grokking-pytorch: The Hitchiker’s Guide to PyTorch
49. PyTorch-Deep-Learning-Minicourse: Minicourse in Deep Learning with PyTorch.
50. pytorch-custom-dataset-examples: Some custom dataset examples for PyTorch
51. Multiplicative LSTM for sequence-based Recommenders
52. deeplearning.ai-pytorch: PyTorch Implementations of Coursera’s Deep Learning(deeplearning.ai) Specialization.
53. MNIST_Pytorch_python_and_capi: This is an example of how to train a MNIST network in Python and run it in c++ with pytorch 1.0

7 论文实现(Paper implementations)

1. google_evolution : This implements one of result networks from Large-scale evolution of image classifiers by Esteban Real, et. al.
2. pyscatwave : Fast Scattering Transform with CuPy/PyTorch,read the paper here
3. scalingscattering : Scaling The Scattering Transform : Deep Hybrid Networks.
4. deep-auto-punctuation : a pytorch implementation of auto-punctuation learned character by character.
5. Realtime_Multi-Person_Pose_Estimation : This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here .
6. PyTorch-value-iteration-networks : PyTorch implementation of the Value Iteration Networks (NIPS '16) paper
7. pytorch_Highway : Highway network implemented in pytorch.
8. pytorch_NEG_loss : NEG loss implemented in pytorch.
9. pytorch_RVAE : Recurrent Variational Autoencoder that generates sequential data implemented in pytorch.
10. pytorch_TDNN : Time Delayed NN implemented in pytorch.
11. eve.pytorch : An implementation of Eve Optimizer, proposed in Imploving Stochastic Gradient Descent with Feedback, Koushik and Hayashi, 2016.
12. e2e-model-learning : Task-based end-to-end model learning.
13. pix2pix-pytorch : PyTorch implementation of “Image-to-Image Translation Using Conditional Adversarial Networks”.
14. Single Shot MultiBox Detector : A PyTorch Implementation of Single Shot MultiBox Detector.
15. DiscoGAN: PyTorch implementation of “Learning to Discover Cross-Domain Relations with Generative Adversarial Networks”
16. official DiscoGAN implementation : Official implementation of “Learning to Discover Cross-Domain Relations with Generative Adversarial Networks”.
17. pytorch-es : This is a PyTorch implementation of Evolution Strategies .
18. piwise : Pixel-wise segmentation on VOC2012 dataset using pytorch.
19. pytorch-dqn : Deep Q-Learning Network in pytorch.
20. neuraltalk2-pytorch : image captioning model in pytorch(finetunable cnn in branch with_finetune)
21. vnet.pytorch : A Pytorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation.
22. pytorch-fcn : PyTorch implementation of Fully Convolutional Networks.
23. WideResNets : 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 .
24. pytorch_highway_networks : Highway networks implemented in PyTorch.
25. pytorch-NeuCom : Pytorch implementation of DeepMind’s differentiable neural computer paper.
26. captionGen : Generate captions for an image using PyTorch.
27. AnimeGAN : A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.
28. Cnn-text classification : This is the implementation of Kim’s Convolutional Neural Networks for Sentence Classification paper in PyTorch.
29. deepspeech2 : Implementation of DeepSpeech2 using Baidu Warp-CTC. Creates a network based on the DeepSpeech2 architecture, trained with the CTC activation function.
30. seq2seq : This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch
31. Asynchronous Advantage Actor-Critic in PyTorch : 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.
32. densenet : 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.
33. nninit : Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin.
34. faster rcnn : 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.
35. doomnet : PyTorch’s version of Doom-net implementing some RL models in ViZDoom environment.
36. flownet : Pytorch implementation of FlowNet by Dosovitskiy et al.
37. sqeezenet : 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.
38. WassersteinGAN: wassersteinGAN in pytorch.
39. optnet : 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.
40. qp solver : A fast and differentiable QP solver for PyTorch. Crafted by Brandon Amos and J. Zico Kolter.
41. Continuous Deep Q-Learning with Model-based Acceleration : Reimplementation of Continuous Deep Q-Learning with Model-based Acceleration.
42. Learning to learn by gradient descent by gradient descent : PyTorch implementation of Learning to learn by gradient descent by gradient descent.
43. fast-neural-style : 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.
44. PytorchNeuralStyleTransfer : Implementation of Neural Style Transfer in Pytorch.
45. Fast Neural Style for Image Style Transform by Pytorch : Fast Neural Style for Image Style Transform by Pytorch .
46. neural style transfer : 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.
47. VIN_PyTorch_Visdom : PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.
48. YOLO2: YOLOv2 in PyTorch.
49. attention-transfer: Attention transfer in pytorch, read the paper here.
50. SVHNClassifier: A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks.
51. pytorch-deform-conv: PyTorch implementation of Deformable Convolution.
52. BEGAN-pytorch: PyTorch implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks.
53. treelstm.pytorch : Tree LSTM implementation in PyTorch.
54. AGE: Code for paper “Adversarial Generator-Encoder Networks” by Dmitry Ulyanov, Andrea Vedaldi and Victor Lempitsky which can be found here
55. ResNeXt.pytorch: Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch.
56. pytorch-rl: Deep Reinforcement Learning with pytorch & visdom
57. Deep-Leafsnap: LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods.
58. pytorch-CycleGAN-and-pix2pix: PyTorch implementation for both unpaired and paired image-to-image translation.
59. A3C-PyTorch:PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
60. pytorch-value-iteration-networks : Pytorch implementation of Value Iteration Networks (NIPS 2016 best paper)
61. PyTorch-Style-Transfer: PyTorch Implementation of Multi-style Generative Network for Real-time Transfer
62. pytorch-deeplab-resnet: pytorch-deeplab-resnet-model.
63. pointnet.pytorch: pytorch implementation for “PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation” https://arxiv.org/abs/1612.00593
64. pytorch-playground: Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet).
65. pytorch-dnc: Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom.
66. pytorch_image_classifier: Minimal But Practical Image Classifier Pipline Using Pytorch, Finetune on ResNet18, Got 99% Accuracy on Own Small Datasets.
67. mnist-svhn-transfer: PyTorch Implementation of CycleGAN and SGAN for Domain Transfer (Minimal).
68. pytorch-yolo2: pytorch-yolo2
69. dni: Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch
70. wgan-gp: A pytorch implementation of Paper “Improved Training of Wasserstein GANs”.
71. pytorch-seq2seq-intent-parsing: Intent parsing and slot filling in PyTorch with seq2seq + attention
72. pyTorch_NCE: An implementation of the Noise Contrastive Estimation algorithm for pyTorch. Working, yet not very efficient.
73. molencoder: Molecular AutoEncoder in PyTorch
74. GAN-weight-norm: Code for “On the Effects of Batch and Weight Normalization in Generative Adversarial Networks”
75. lgamma: Implementations of polygamma, lgamma, and beta functions for PyTorch
76. bigBatch : Code used to generate the results appearing in “Train longer, generalize better: closing the generalization gap in large batch training of neural networks”
77. rl_a3c_pytorch: Reinforcement learning with implementation of A3C LSTM for Atari 2600.
78. pytorch-retraining: Transfer Learning Shootout for PyTorch’s model zoo (torchvision)
79. nmp_qc: Neural Message Passing for Computer Vision
80. grad-cam: Pytorch implementation of Grad-CAM
81. pytorch-trpo: PyTorch Implementation of Trust Region Policy Optimization (TRPO)
82. pytorch-explain-black-box: PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation
83. vae_vpflows: Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling https://jmtomczak.github.io/deebmed.html
84. relational-networks: Pytorch implementation of “A simple neural network module for relational reasoning” (Relational Networks) https://arxiv.org/pdf/1706.01427.pdf
85. vqa.pytorch: Visual Question Answering in Pytorch
86. end-to-end-negotiator: Deal or No Deal? End-to-End Learning for Negotiation Dialogues
87. odin-pytorch: Principled Detection of Out-of-Distribution Examples in Neural Networks.
88. FreezeOut: Accelerate Neural Net Training by Progressively Freezing Layers.
89. ARAE: Code for the paper “Adversarially Regularized Autoencoders for Generating Discrete Structures” by Zhao, Kim, Zhang, Rush and LeCun.
90. forward-thinking-pytorch: Pytorch implementation of “Forward Thinking: Building and Training Neural Networks One Layer at a Time” https://arxiv.org/pdf/1706.02480.pdf
91. context_encoder_pytorch: PyTorch Implement of Context Encoders
92. attention-is-all-you-need-pytorch: A PyTorch implementation of the Transformer model in “Attention is All You Need”.https://github.com/thnkim/OpenFacePytorch
93. OpenFacePytorch: PyTorch module to use OpenFace’s nn4.small2.v1.t7 model
94. neural-combinatorial-rl-pytorch: PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.
    95.pytorch-nec: PyTorch Implementation of Neural Episodic Control (NEC)
95. seq2seq.pytorch: Sequence-to-Sequence learning using PyTorch
96. Pytorch-Sketch-RNN: a pytorch implementation of arxiv.org/abs/1704.03477
97. pytorch-pruning: PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
98. DrQA : A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.
99. YellowFin_Pytorch : auto-tuning momentum SGD optimizer
100. samplernn-pytorch : PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model.
101. AEGeAN: Deeper DCGAN with AE stabilization
102. /pytorch-SRResNet: pytorch implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802v2
103. vsepp: Code for the paper “VSE++: Improved Visual Semantic Embeddings”
104. Pytorch-DPPO: Pytorch implementation of Distributed Proximal Policy Optimization: arxiv.org/abs/1707.02286
105. UNIT: PyTorch Implementation of our Coupled VAE-GAN algorithm for Unsupervised Image-to-Image Translation
106. efficient_densenet_pytorch: A memory-efficient implementation of DenseNets
107. tsn-pytorch: Temporal Segment Networks (TSN) in PyTorch.
108. SMASH: An experimental technique for efficiently exploring neural architectures.
109. pytorch-retinanet: RetinaNet in PyTorch
110. biogans: Implementation supporting the ICCV 2017 paper “GANs for Biological Image Synthesis”.
111. Semantic Image Synthesis via Adversarial Learning: A PyTorch implementation of the paper “Semantic Image Synthesis via Adversarial Learning” in ICCV 2017.
112. fmpytorch: A PyTorch implementation of a Factorization Machine module in cython.
113. ORN: A PyTorch implementation of the paper “Oriented Response Networks” in CVPR 2017.
114. pytorch-maml: PyTorch implementation of MAML: arxiv.org/abs/1703.03400
115. pytorch-generative-model-collections: Collection of generative models in Pytorch version.
116. vqa-winner-cvprw-2017: Pytorch Implementation of winner from VQA Chllange Workshop in CVPR’17.
117. tacotron_pytorch : PyTorch implementation of Tacotron speech synthesis model.
118. pspnet-pytorch: PyTorch implementation of PSPNet segmentation network
119. LM-LSTM-CRF: Empower Sequence Labeling with Task-Aware Language Model http://arxiv.org/abs/1709.04109
120. face-alignment: Pytorch implementation of the paper “How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)”, ICCV 2017
121. DepthNet: PyTorch DepthNet Training on Still Box dataset.
122. EDSR-PyTorch: PyTorch version of the paper ‘Enhanced Deep Residual Networks for Single Image Super-Resolution’ (CVPRW 2017)
123. e2c-pytorch: Embed to Control implementation in PyTorch.
124. 3D-ResNets-PyTorch: 3D ResNets for Action Recognition.
125. bandit-nmt: 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.
126. pytorch-a2c-ppo-acktr: 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).
127. zalando-pytorch: Various experiments on the
     Fashion-MNIST dataset from Zalando.
128. sphereface_pytorch: A PyTorch Implementation of SphereFace.
129. Categorical DQN: A PyTorch Implementation of Categorical DQN from A Distributional Perspective on Reinforcement Learning.
130. pytorch-ntm: pytorch ntm implementation.
131. mask_rcnn_pytorch: Mask RCNN in PyTorch.
132. graph_convnets_pytorch: PyTorch implementation of graph ConvNets, NIPS’16
133. pytorch-faster-rcnn: A pytorch implementation of faster RCNN detection framework based on Xinlei Chen’s tf-faster-rcnn.
134. torchMoji: A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.
135. semantic-segmentation-pytorch: Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
136. pytorch-qrnn: PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA’s cuDNN LSTM
137. pytorch-sgns: Skipgram Negative Sampling in PyTorch.
138. SfmLearner-Pytorch : Pytorch version of SfmLearner from Tinghui Zhou et al.
139. deformable-convolution-pytorch: PyTorch implementation of Deformable Convolution.
140. skip-gram-pytorch: A complete pytorch implementation of skipgram model (with subsampling and negative sampling). The embedding result is tested with Spearman’s rank correlation.
141. stackGAN-v2: Pytorch implementation for reproducing StackGAN_v2 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.
142. self-critical.pytorch: Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning.
143. pygcn: Graph Convolutional Networks in PyTorch.
144. dnc: Differentiable Neural Computers, for Pytorch
145. prog_gans_pytorch_inference: PyTorch inference for “Progressive Growing of GANs” with CelebA snapshot.
146. pytorch-capsule: Pytorch implementation of Hinton’s Dynamic Routing Between Capsules.
147. PyramidNet-PyTorch: A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, arxiv.org/abs/1610.02915)
148. radio-transformer-networks: A PyTorch implementation of Radio Transformer Networks from the paper “An Introduction to Deep Learning for the Physical Layer”. arxiv.org/abs/1702.00832
149. honk: PyTorch reimplementation of Google’s TensorFlow CNNs for keyword spotting.
150. DeepCORAL: A PyTorch implementation of ‘Deep CORAL: Correlation Alignment for Deep Domain Adaptation.’, ECCV 2016
151. pytorch-pose: A PyTorch toolkit for 2D Human Pose Estimation.
152. lang-emerge-parlai: Implementation of EMNLP 2017 Paper “Natural Language Does Not Emerge ‘Naturally’ in Multi-Agent Dialog” using PyTorch and ParlAI
153. Rainbow: Rainbow: Combining Improvements in Deep Reinforcement Learning
154. pytorch_compact_bilinear_pooling v1: This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch.
155. CompactBilinearPooling-Pytorch v2: (Yang Gao, et al.) A Pytorch Implementation for Compact Bilinear Pooling.
156. FewShotLearning: Pytorch implementation of the paper “Optimization as a Model for Few-Shot Learning”
157. meProp: Codes for “meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting”.
158. SFD_pytorch: A PyTorch Implementation of Single Shot Scale-invariant Face Detector.
159. GradientEpisodicMemory: Continuum Learning with GEM: Gradient Episodic Memory. https://arxiv.org/abs/1706.08840
160. DeblurGAN: Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks.
161. StarGAN: StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Tranlsation.
162. CapsNet-pytorch: PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules.
163. CondenseNet: CondenseNet: An Efficient DenseNet using Learned Group Convolutions.
164. deep-image-prior: Image restoration with neural networks but without learning.
165. deep-head-pose: Deep Learning Head Pose Estimation using PyTorch.
166. Random-Erasing: This code has the source code for the paper “Random Erasing Data Augmentation”.
167. FaderNetworks: Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017
168. FlowNet 2.0: FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
169. pix2pixHD: Synthesizing and manipulating 2048x1024 images with conditional GANs tcwang0509.github.io/pix2pixHD
170. pytorch-smoothgrad: SmoothGrad implementation in PyTorch
171. RetinaNet: An implementation of RetinaNet in PyTorch.
172. faster-rcnn.pytorch: This project is a faster faster R-CNN implementation, aimed to accelerating the training of faster R-CNN object detection models.
173. mixup_pytorch: A PyTorch implementation of the paper Mixup: Beyond Empirical Risk Minimization in PyTorch.
174. inplace_abn: In-Place Activated BatchNorm for Memory-Optimized Training of DNNs
175. pytorch-pose-hg-3d: PyTorch implementation for 3D human pose estimation
176. nmn-pytorch: Neural Module Network for VQA in Pytorch.
177. bytenet: Pytorch implementation of bytenet from “Neural Machine Translation in Linear Time” paper
178. bottom-up-attention-vqa: vqa, bottom-up-attention, pytorch
179. yolo2-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.
180. reseg-pytorch: PyTorch Implementation of ReSeg (arxiv.org/pdf/1511.07053.pdf)
181. binary-stochastic-neurons: Binary Stochastic Neurons in PyTorch.
182. pytorch-pose-estimation: PyTorch Implementation of Realtime Multi-Person Pose Estimation project.
183. interaction_network_pytorch: Pytorch Implementation of Interaction Networks for Learning about Objects, Relations and Physics.
184. NoisyNaturalGradient: Pytorch Implementation of paper “Noisy Natural Gradient as Variational Inference”.
185. ewc.pytorch: An implementation of Elastic Weight Consolidation (EWC), proposed in James Kirkpatrick et al. Overcoming catastrophic forgetting in neural networks 2016(10.1073/pnas.1611835114).
186. pytorch-zssr: PyTorch implementation of 1712.06087 “Zero-Shot” Super-Resolution using Deep Internal Learning
187. deep_image_prior: An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch.
188. pytorch-transformer: pytorch implementation of Attention is all you need.
189. DeepRL-Grounding: This is a PyTorch implementation of the AAAI-18 paper Gated-Attention Architectures for Task-Oriented Language Grounding
190. deep-forecast-pytorch: Wind Speed Prediction using LSTMs in PyTorch (arxiv.org/pdf/1707.08110.pdf)
191. cat-net: Canonical Appearance Transformations
192. minimal_glo: Minimal PyTorch implementation of Generative Latent Optimization from the paper “Optimizing the Latent Space of Generative Networks”
193. LearningToCompare-Pytorch: Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning.
194. poincare-embeddings: PyTorch implementation of the NIPS-17 paper “Poincaré Embeddings for Learning Hierarchical Representations”.
195. pytorch-trpo(Hessian-vector product version): This is a PyTorch implementation of “Trust Region Policy Optimization (TRPO)” with exact Hessian-vector product instead of finite differences approximation.
196. ggnn.pytorch: A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN).
197. visual-interaction-networks-pytorch: This’s an implementation of deepmind Visual Interaction Networks paper using pytorch
198. adversarial-patch: PyTorch implementation of adversarial patch.
199. Prototypical-Networks-for-Few-shot-Learning-PyTorch: Implementation of Prototypical Networks for Few Shot Learning (arxiv.org/abs/1703.05175) in Pytorch
200. Visual-Feature-Attribution-Using-Wasserstein-GANs-Pytorch: Implementation of Visual Feature Attribution using Wasserstein GANs (arxiv.org/abs/1711.08998) in PyTorch.
201. PhotographicImageSynthesiswithCascadedRefinementNetworks-Pytorch: Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
202. ENAS-pytorch: PyTorch implementation of “Efficient Neural Architecture Search via Parameters Sharing”.
203. Neural-IMage-Assessment: A PyTorch Implementation of Neural IMage Assessment.
204. proxprop: Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps.
205. FastPhotoStyle: A Closed-form Solution to Photorealistic Image Stylization
206. Deep-Image-Analogy-PyTorch: A python implementation of Deep-Image-Analogy based on pytorch.
207. Person-reID_pytorch: PyTorch for Person re-ID.
208. pt-dilate-rnn: Dilated RNNs in pytorch.
209. pytorch-i-revnet: Pytorch implementation of i-RevNets.
210. OrthNet: TensorFlow and PyTorch layers for generating Orthogonal Polynomials.
211. DRRN-pytorch: An implementation of Deep Recursive Residual Network for Super Resolution (DRRN), CVPR 2017
212. shampoo.pytorch: An implementation of shampoo.
213. Neural-IMage-Assessment 2: A PyTorch Implementation of Neural IMage Assessment.
214. TCN: Sequence modeling benchmarks and temporal convolutional networks locuslab/TCN
215. DCC: This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper.
216. packnet: Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning arxiv.org/abs/1711.05769
217. PyTorch-progressive_growing_of_gans: PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.
218. nonauto-nmt: PyTorch Implementation of “Non-Autoregressive Neural Machine Translation”
219. PyTorch-GAN: PyTorch implementations of Generative Adversarial Networks.
220. PyTorchWavelets: PyTorch implementation of the wavelet analysis found in Torrence and Compo (1998)
221. pytorch-made: MADE (Masked Autoencoder Density Estimation) implementation in PyTorch
222. VRNN: Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data.
223. flow: Pytorch implementation of ICLR 2018 paper Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge.
224. deepvoice3_pytorch: PyTorch implementation of convolutional networks-based text-to-speech synthesis models
225. psmm: imlementation of the the Pointer Sentinel Mixture Model, as described in the paper by Stephen Merity et al.
226. tacotron2: Tacotron 2 - PyTorch implementation with faster-than-realtime inference.
227. AccSGD: Implements pytorch code for the Accelerated SGD algorithm.
228. QANet-pytorch: an implementation of QANet with PyTorch (EM/F1 = 70.5/77.2 after 20 epoches for about 20 hours on one 1080Ti card.)
229. ConvE: Convolutional 2D Knowledge Graph Embeddings
230. Structured-Self-Attention:
     Implementation for the paper A Structured Self-Attentive Sentence Embedding, which is published in ICLR 2017: arxiv.org/abs/1703.03130 .
231. graphsage-simple: Simple reference implementation of GraphSAGE.
232. Detectron.pytorch: A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
233. R2Plus1D-PyTorch: PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper “A Closer Look at Spatiotemporal Convolutions for Action Recognition”
234. StackNN: A PyTorch implementation of differentiable stacks for use in neural networks.
235. translagent: Code for Emergent Translation in Multi-Agent Communication.
236. ban-vqa: Bilinear attention networks for visual question answering.
237. pytorch-openai-transformer-lm: 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.
238. T2F: Text-to-Face generation using Deep Learning. This project combines two of the recent architectures StackGAN and ProGAN for synthesizing faces from textual descriptions.
239. pytorch - fid: A Port of Fréchet Inception Distance (FID score) to PyTorch
240. vae_vpflows:Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling jmtomczak.github.io/deebmed.html
241. CoordConv-pytorch: Pytorch implementation of CoordConv introduced in ‘An intriguing failing of convolutional neural networks and the CoordConv solution’ paper. (arxiv.org/pdf/1807.03247.pdf)
242. SDPoint: Implementation of “Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks”, published in CVPR 2018.
243. SRDenseNet-pytorch: SRDenseNet-pytorch（ICCV_2017）
244. GAN_stability: Code for paper “Which Training Methods for GANs do actually Converge? (ICML 2018)”
245. Mask-RCNN: A PyTorch implementation of the architecture of Mask RCNN, serves as an introduction to working with PyTorch
246. pytorch-coviar: Compressed Video Action Recognition
247. PNASNet.pytorch: PyTorch implementation of PNASNet-5 on ImageNet.
248. NALU-pytorch: Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units arxiv.org/pdf/1808.00508.pdf
249. LOLA_DiCE: Pytorch implementation of LOLA (arxiv.org/abs/1709.04326) using DiCE (arxiv.org/abs/1802.05098)
250. generative-query-network-pytorch: Generative Query Network (GQN) in PyTorch as described in “Neural Scene Representation and Rendering”
251. pytorch_hmax: Implementation of the HMAX model of vision in PyTorch.
252. FCN-pytorch-easiest: trying to be the most easiest and just get-to-use pytorch implementation of FCN (Fully Convolotional Networks)
253. transducer: A Fast Sequence Transducer Implementation with PyTorch Bindings.
254. AVO-pytorch: Implementation of Adversarial Variational Optimization in PyTorch.
255. HCN-pytorch: A pytorch reimplementation of { Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation }.
256. binary-wide-resnet: PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnel (ICLR 2018)
257. piggyback: Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights arxiv.org/abs/1801.06519
258. vid2vid: Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
259. poisson-convolution-sum: Implements an infinite sum of poisson-weighted convolutions
260. tbd-nets: PyTorch implementation of “Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning” arxiv.org/abs/1803.05268
261. attn2d: Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
262. yolov3: YOLOv3: Training and inference in PyTorch pjreddie.com/darknet/yolo
263. deep-dream-in-pytorch: Pytorch implementation of the DeepDream computer vision algorithm.
264. pytorch-flows: PyTorch implementations of algorithms for density estimation
265. quantile-regression-dqn-pytorch: Quantile Regression DQN a Minimal Working Example
266. relational-rnn-pytorch: An implementation of DeepMind’s Relational Recurrent Neural Networks in PyTorch.
267. DEXTR-PyTorch: Deep Extreme Cut http://www.vision.ee.ethz.ch/~cvlsegmentation/dextr
268. PyTorch_GBW_LM: PyTorch Language Model for Google Billion Word Dataset.
269. Pytorch-NCE: The Noise Contrastive Estimation for softmax output written in Pytorch
270. generative-models: Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN.
271. convnet-aig: PyTorch implementation for Convolutional Networks with Adaptive Inference Graphs.
272. integrated-gradient-pytorch: This is the pytorch implementation of the paper - Axiomatic Attribution for Deep Networks.
273. MalConv-Pytorch: Pytorch implementation of MalConv.
     275, trellisnet: Trellis Networks for Sequence Modeling

8 PyTorch 其他项目

1. the-incredible-pytorch : The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
2. generative models : Collection of generative models, e.g. GAN, VAE in Tensorflow, Keras, and Pytorch. http://wiseodd.github.io
3. pytorch vs tensorflow : an informative thread on reddit.
4. Pytorch discussion forum
5. pytorch notebook: docker-stack : A project similar to Jupyter Notebook Scientific Python Stack
6. drawlikebobross: Draw like Bob Ross using the power of Neural Networks (With PyTorch)!
7. pytorch-tvmisc: Totally Versatile Miscellanea for Pytorch
8. pytorch-a3c-mujoco: Implement A3C for Mujoco gym envs.
9. PyTorch in 5 Minutes.
10. pytorch_chatbot: A Marvelous ChatBot implemented using PyTorch.
11. malmo-challenge: Malmo Collaborative AI Challenge - Team Pig Catcher
12. sketchnet: A model that takes an image and generates Processing source code to regenerate that image
13. Deep-Learning-Boot-Camp: A nonprofit community run, 5-day Deep Learning Bootcamp http://deep-ml.com.
14. Amazon_Forest_Computer_Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks. kaggle competition.
15. AlphaZero_Gomoku: An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
16. pytorch-cv: Repo for Object Detection, Segmentation & Pose Estimation.
17. deep-person-reid: Pytorch implementation of deep person re-identification approaches.
18. pytorch-template: PyTorch template project
19. Deep Learning With Pytorch TextBook A practical guide to build neural network models in text and vision using PyTorch. Purchase on Amazon github code repo
20. compare-tensorflow-pytorch: Compare outputs between layers written in Tensorflow and layers written in Pytorch.
21. hasktorch: Tensors and neural networks in Haskell
22. Deep Learning With Pytorch Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch.
23. nimtorch: PyTorch - Python + Nim
24. derplearning: Self Driving RC Car Code.