Ecosystem

If your project implements a paper, represents other use-cases not covered in our official tutorials, Kaggle competition’s code, or just your code presents interesting results and uses PyTorch-Ignite. We would like to add your project to this list, so please open an issue here: https://github.com/pytorch-ignite/pytorch-ignite.ai/issues with brief description of the project.

The list below is unexhausted list of references that we are aware of.

Research Papers

• BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
• A Model to Search for Synthesizable Molecules
• Localised Generative Flows
• Extracting T Cell Function and Differentiation Characteristics from the Biomedical Literature
• Variational Information Distillation for Knowledge Transfer
• XPersona: Evaluating Multilingual Personalized Chatbot
• CNN-CASS: CNN for Classification of Coronary Artery Stenosis Score in MPR Images
• Bridging Text and Video: A Universal Multimodal Transformer for Video-Audio Scene-Aware Dialog
• Adversarial Decomposition of Text Representation
• Uncertainty Estimation Using a Single Deep Deterministic Neural Network
• DeepSphere: a graph-based spherical CNN
• Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality Assessment
• Unified Quality Assessment of In-the-Wild Videos with Mixed Datasets Training
• Deep Signature Transforms
• Neural CDEs for Long Time-Series via the Log-ODE Method
• Volumetric Grasping Network
• Mood Classification using Listening Data
• Deterministic Uncertainty Estimation (DUE)
• PyTorch-Hebbian: facilitating local learning in a deep learning framework
• Stochastic Weight Matrix-Based Regularization Methods for Deep Neural Networks
• Learning explanations that are hard to vary
• The role of disentanglement in generalisation
• A Probabilistic Programming Approach to Protein Structure Superposition
• PadChest: A large chest x-ray image dataset with multi-label annotated reports
• Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data

Blog articles, tutorials, books

• State-of-the-Art Conversational AI with Transfer Learning
• Tutorial on Transfer Learning in NLP held at NAACL 2019
• Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt
• Once Upon a Repository: How to Write Readable, Maintainable Code with PyTorch
• The Hero Rises: Build Your Own SSD
• Using Optuna to Optimize PyTorch Ignite Hyperparameters

Toolkits

• Project MONAI - AI Toolkit for Healthcare Imaging
• DeepSeismic - Deep Learning for Seismic Imaging and Interpretation
• Nussl - a flexible, object-oriented Python audio source separation library
• xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs
• PyTorch Adapt - A fully featured and modular domain adaptation library
• gnina-torch: PyTorch implementation of GNINA scoring function
• PyTorch-Ignite Code-generator: The easiest way to create your training scripts with PyTorch-Ignite

Others

• Implementation of “Attention is All You Need” paper
• Implementation of DropBlock: A regularization method for convolutional networks in PyTorch
• Kaggle Kuzushiji Recognition: 2nd place solution
• Unsupervised Data Augmentation experiments in PyTorch
• Hyperparameters tuning with Optuna
• Logging with ChainerUI
• FixMatch experiments in PyTorch and Ignite (CTA dataaug policy)
• Kaggle Birdcall Identification Competition: 1st place solution
• Logging with Aim - An open-source experiment tracker

See other projects at “Used by”.