README.md

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This is inspired by the helpful Awesome TensorFlow repository where this repository would hold tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch.

Tutorials

• Official PyTorch Tutorials
  1. Deep Learning with PyTorch: a 60-minute blitz
     • A perfect introduction to PyTorch's torch, autograd, nn and optim APIs
     • If you are a former Torch user, you can check out this instead: Introduction to PyTorch for former Torchies
  2. Custom C extensions
     • Write your own C code that interfaces into PyTorch via FFI
  3. Writing your own neural network module that uses numpy and scipy
  4. Reinforcement (Q-)Learning with PyTorch
• Official PyTorch Examples
  • MNIST Convnets
  • Word level Language Modeling using LSTM RNNs
  • Training Imagenet Classifiers with Residual Networks
  • Generative Adversarial Networks (DCGAN)
  • Variational Auto-Encoders
  • Superresolution using an efficient sub-pixel convolutional neural network
  • Hogwild training of shared ConvNets across multiple processes on MNIST
  • Training a CartPole to balance in OpenAI Gym with actor-critic
  • Natural Language Inference (SNLI) with GloVe vectors, LSTMs, and torchtext
• Practical PyTorch
  • This focuses on using RNNs for NLP
  • Classifying Names with a Character-Level RNN
  • Generating Names with a Character-Level RNN
  • Translation with a Sequence to Sequence Network and Attention
• Simple Examples to Introduce PyTorch
• Mini Tutorials in PyTorch
  • Tensor Multiplication, Linear Regresison, Logistic Regression, Neural Network, Modern Neural Network, and Convolutional Neural Network

Papers in PyTorch

• Learning to learn by gradient descent by gradient descent
• Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer
• Wasserstein GAN
• Densely Connected Convolutional Networks
• A Neural Algorithm of Artistic Style
• Very Deep Convolutional Networks for Large-Scale Image Recognition
  • VGG model in PyTorch.
• SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
• Network In Network
• Deep Residual Learning for Image Recognition
  • ResNet model in PyTorch.
• Wide Residual Networks
  • Wide ResNet model in PyTorch
• Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
• FlowNet: Learning Optical Flow with Convolutional Networks
• Asynchronous Methods for Deep Reinforcement Learning
• Perceptual Losses for Real-Time Style Transfer and Super-Resolution

Projects in Pytorch

• Reinforcement learning models in ViZDoom environment with PyTorch
• Collection of Generative Models with PyTorch
  • Generative Adversarial Nets (GAN)
    1. Vanilla GAN
    2. Conditional GAN
    3. InfoGAN
    4. Wasserstein GAN
    5. Mode Regularized GAN
  • Variational Autoencoder (VAE)
    1. Vanilla VAE
    2. Conditional VAE
    3. Denoising VAE
    4. Adversarial Autoencoder
    5. Adversarial Variational Bayes
• Neuraltalk 2, Image Captioning Model, in PyTorch
• Recurrent Neural Networks for Sentiment Analysis (Aspect-Based) on SemEval 2014
• PyTorch Image Classification with Kaggle Dogs vs Cats Dataset

Community

• PyTorch Discussion Forum
  • This is actively maintained by Adam Paszke
• StackOverflow PyTorch Tags

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.