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.
pytorch-cnn-finetune: Fine-tune pretrained Convolutional Neural Networks with PyTorch.
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
Probabilistic/Generative Libraries:
ptstat: Probabilistic Programming and Statistical Inference in PyTorch
pyro: Deep universal probabilistic programming with Python and PyTorch http://pyro.ai
probtorch: Probabilistic Torch is library for deep generative models that extends PyTorch.
paysage: Unsupervised learning and generative models in python/pytorch.
pyvarinf: Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch.
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.
torch-sampling : This package provides a set of transforms and data structures for sampling from in-memory or out-of-memory data.
torchcraft-py : Python wrapper for TorchCraft, a bridge between Torch and StarCraft for AI research.
aorun : Aorun intend to be a Keras with PyTorch as backend.
pytorch-extension: This is a CUDA extension for PyTorch which computes the Hadamard product of two tensors.
tensorboard-pytorch: This module saves PyTorch tensors in tensorboard format for inspection. Currently supports scalar, image, audio, histogram features in tensorboard.
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.
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.
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.
convnet : This is a complete training example for Deep Convolutional Networks on various datasets (ImageNet, Cifar10, Cifar100, MNIST).
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.
pytorch_tutoria-quick: Quick PyTorch introduction and tutorial. Targets computer vision, graphics and machine learning researchers eager to try a new framework.
pytorch-NeuCom : Pytorch implementation of DeepMind's differentiable neural computer paper.
captionGen : Generate captions for an image using PyTorch.
AnimeGAN : A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.
Cnn-text classification : This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch.
deepspeech2 : Implementation of DeepSpeech2 using Baidu Warp-CTC. Creates a network based on the DeepSpeech2 architecture, trained with the CTC activation function.
seq2seq : This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch
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.
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.
nninit : Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin.
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.
doomnet : PyTorch's version of Doom-net implementing some RL models in ViZDoom environment.
flownet : Pytorch implementation of FlowNet by Dosovitskiy et al.
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.
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.
qp solver : A fast and differentiable QP solver for PyTorch. Crafted by Brandon Amos and J. Zico Kolter.
GAN-weight-norm: Code for "On the Effects of Batch and Weight Normalization in Generative Adversarial Networks"
lgamma: Implementations of polygamma, lgamma, and beta functions for PyTorch
bigBatch : Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"
rl_a3c_pytorch: Reinforcement learning with implementation of A3C LSTM for Atari 2600.
pytorch-retraining: Transfer Learning Shootout for PyTorch's model zoo (torchvision)
nmp_qc: Neural Message Passing for Computer Vision
OpenFacePytorch: PyTorch module to use OpenFace's nn4.small2.v1.t7 model
neural-combinatorial-rl-pytorch: PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.
95.pytorch-nec: PyTorch Implementation of Neural Episodic Control (NEC)
seq2seq.pytorch: Sequence-to-Sequence learning using PyTorch
Pytorch-Sketch-RNN: a pytorch implementation of arxiv.org/abs/1704.03477
pytorch-pruning: PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
DrQA : A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.
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
DepthNet: PyTorch DepthNet Training on Still Box dataset.
EDSR-PyTorch: PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
e2c-pytorch: Embed to Control implementation in PyTorch.
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.
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).
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.
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.
self-critical.pytorch: Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning.
pytorch-capsule: Pytorch implementation of Hinton's Dynamic Routing Between Capsules.
PyramidNet-PyTorch: A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, arxiv.org/abs/1610.02915)
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
honk: PyTorch reimplementation of Google's TensorFlow CNNs for keyword spotting.
DeepCORAL: A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation.', ECCV 2016
pytorch-pose: A PyTorch toolkit for 2D Human Pose Estimation.
lang-emerge-parlai: Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI
Rainbow: Rainbow: Combining Improvements in Deep Reinforcement Learning
pytorch_compact_bilinear_pooling v1: This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch.
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.
reseg-pytorch: PyTorch Implementation of ReSeg (arxiv.org/pdf/1511.07053.pdf)
pytorch-pose-estimation: PyTorch Implementation of Realtime Multi-Person Pose Estimation project.
interaction_network_pytorch: Pytorch Implementation of Interaction Networks for Learning about Objects, Relations and Physics.
NoisyNaturalGradient: Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference".
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).
pytorch-zssr: PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning
deep_image_prior: An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch.
minimal_glo: Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"
LearningToCompare-Pytorch: Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning.
poincare-embeddings: PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations".
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.
ggnn.pytorch: A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN).
Structured-Self-Attention:
Implementation for the paper A Structured Self-Attentive Sentence Embedding, which is published in ICLR 2017: arxiv.org/abs/1703.03130 .
Detectron.pytorch: A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
R2Plus1D-PyTorch: PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition"
StackNN: A PyTorch implementation of differentiable stacks for use in neural networks.
translagent: Code for Emergent Translation in Multi-Agent Communication.
ban-vqa: Bilinear attention networks for visual question answering.
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.
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.
Pytorch elsewhere
the-incredible-pytorch : The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.