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

Overview


This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch. Feel free to make a pull request to contribute to this list.

Table Of Contents

Tabular Data

Tutorials

Visualization

Explainability

Object Detection

Long-Tailed / Out-of-Distribution Recognition

Activation Functions

Energy-Based Learning

Missing Data

Architecture Search

Optimization

Quantization

Quantum Machine Learning

Neural Network Compression

Facial, Action and Pose Recognition

Super resolution

Synthetesizing Views

Voice

Medical

3D Segmentation, Classification and Regression

Video Recognition

Recurrent Neural Networks (RNNs)

Convolutional Neural Networks (CNNs)

Segmentation

Geometric Deep Learning: Graph & Irregular Structures

Sorting

Ordinary Differential Equations Networks

Multi-task Learning

GANs, VAEs, and AEs

Unsupervised Learning

Adversarial Attacks

Style Transfer

Image Captioning

Transformers

Similarity Networks and Functions

Reasoning

General NLP

Question and Answering

Speech Generation and Recognition

Document and Text Classification

Text Generation

Translation

Sentiment Analysis

Deep Reinforcement Learning

Deep Bayesian Learning and Probabilistic Programmming

Spiking Neural Networks

Anomaly Detection

Regression Types

Time Series

Synthetic Datasets

Neural Network General Improvements

DNN Applications in Chemistry and Physics

New Thinking on General Neural Network Architecture

Linear Algebra

API Abstraction

Low Level Utilities

PyTorch Utilities

PyTorch Video Tutorials

Datasets

Community

Links to This Repository

To be Classified

Contributions

Do feel free to contribute!

You can raise an issue or submit a pull request, whichever is more convenient for you. The guideline is simple: just follow the format of the previous bullet point.

Comments
  • Image Captioning paper

    Image Captioning paper

    Hello, Thanks for the amazing collection. But I would like to point out one thing - in the image captioning topic there are three mentioned papers which are correct if we see the captioning field but since this collection is about pytorch I was confuse why the 'DenceCap' paper is there because the paper is on lua, lua with torch.

    opened by AnukritiSinghh 6
  • Tabular Data Category : pytorch-tabnet

    Tabular Data Category : pytorch-tabnet

    To my surprise there is no tabular data category in the list, while it’s probably the most common type of data you encounter in Machine Learning.

    I would suggest adding pytorch-tabnet to the newly created « Tabular Data » category. Pytorch-tabnet allows easy training of TabNet model (attention based model for tabular data) for binary/multi-class classification, regression and multi-target regression.

    Hope you’ll like the repo and share the love!

    https://github.com/dreamquark-ai/tabnet

    Thanks!

    opened by Optimox 3
  • Added Catalyst framework

    Added Catalyst framework

    Catalyst 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.

    Features

    • Universal train/inference loop.
    • Configuration files for model/data hyperparameters.
    • Reproducibility – all source code and environment variables will be saved.
    • Callbacks – reusable train/inference pipeline parts.
    • Training stages support.
    • Easy customization.
    • PyTorch best practices (SWA, AdamW, 1Cycle, FP16 and more).

    Structure

    • DL – runner for training and inference, all of the classic machine learning and computer vision metrics and a variety of callbacks for training, validation, and inference of neural networks.
    • RL – scalable Reinforcement Learning, on-policy & off-policy algorithms and their improvements with distributed training support.
    • contrib - additional modules contributed by Catalyst users.
    • data - useful tools and scripts for data processing.
    opened by TezRomacH 3
  • Unsupervised Learning of Depth and Ego-Motion from Video was not originally implemented in pytorch

    Unsupervised Learning of Depth and Ego-Motion from Video was not originally implemented in pytorch

    Hello, thanks a lot for your nice repo !

    You introduced the paper "Unsupervised Learning of Depth and Ego-Motion from Video" and the implementation I've done (https://github.com/ClementPinard/SfmLearner-Pytorch) as "Papers Originally Implemented with PyTorch" , but the original implementation is in Tensorflow, made by tinghuiz : https://github.com/tinghuiz/SfMLearner

    bug 
    opened by ClementPinard 2
  • Add torchensemble

    Add torchensemble

    Hi, here is a useful toolkit for improving the performance of PyTorch models via ensemble learning ;-) I will take efforts to make sure that it is under active developments. Thanks!

    opened by xuyxu 1
  • Update README.html

    Update README.html

    adding a paper "CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features" in image captioning section (replacing DenseCap)

    opened by AnukritiSinghh 1
  • Consider adding MedicalZoo Pytorch

    Consider adding MedicalZoo Pytorch

    Hello, would you please consider adding MedicalZoo Pytorch in the medical section? It is a deep learning framework for multi-modal 2D/3D medical image segmentation.

    Link: https://github.com/black0017/MedicalZooPytorch

    Great work by the way!

    N.A.

    opened by black0017 1
  • Add FlashTorch and Lucent under Visualization

    Add FlashTorch and Lucent under Visualization

    Thanks for the compilation of PyTorch resources! I've added two more visualization libraries FlashTorch and Lucent (disclaimer I am the owner of Lucent)

    opened by greentfrapp 1
  • add kornia vision library

    add kornia vision library

    this PR adds kornia to utilities section. However, I really miss a section for image pre-processing since there are quite a few libraries in that purpose: torchvision, albumentation, dali, etc. Missing also high level section for training frameworks like skorch, lightning, or ignite. Good recap though !

    opened by edgarriba 1
  • Return the Catalyst framework

    Return the Catalyst framework

    Catalyst was accidentally removed in this commit so I return it.

    As I previously noticed at #85 :

    Catalyst – 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.

    Catalyst is used in Kaggle, Weights & Biases and ml-workspace.

    Features

    • Universal train/inference loop.
    • Configuration files for model/data hyperparameters.
    • Reproducibility – all source code and environment variables will be saved.
    • Callbacks – reusable train/inference pipeline parts.
    • Training stages support.
    • Easy customization.
    • PyTorch best practices (SWA, AdamW, OneCycle, Ranger optimizer, FP16 and more).
    opened by TezRomacH 1
  • Split Into Categories

    Split Into Categories

    I'll be splitting the page into sub-categories like meta-learning, deep reinforcement learning, GANs, etc.

    Feel free to provide your suggestions. I'm doing this because this is getting massive and hard to find things quickly without knowing what you're looking for.

    enhancement 
    opened by ritchieng 1
  • Explain each category?

    Explain each category?

    This list looks amazing! One thing that I think would be cool for newbies is to explain the category in a paragraph or two.

    For example, what is 'Architecture Search' and what is it useful for.

    enhancement 
    opened by sradu 3
Owner
Ritchie Ng
About: ritchieng.live • Notes: ritchieng.com • Guides: deeplearningwizard.com
Ritchie Ng
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