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causal-ml

Must-read papers and resources related to causal inference and machine (deep) learning

causallib

A Python package for modular causal inference analysis and model evaluations

causalml

Uplift modeling and causal inference with machine learning algorithms

compressionvae

General-purpose dimensionality reduction and manifold learning tool based on Variational Autoencoder, implemented in TensorFlow.

deep-learning-uncertainty

Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deep-reinforcement-learning-with-pytorch

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

deep-transfer-learning-1

A collection of implementations of deep domain adaptation algorithms

deepbayes-2019

Practical assignments of the Deep|Bayes summer school 2019

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

deepsuperlearner

DeepSuperLearner - Python implementation of the deep ensemble algorithm

denoising

diffusion_models

A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch

dig

A library for graph deep learning research

dimig

Inferring disease-associated miRNAs

e3_diffusion_for_molecules

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

freia

Framework for Easily Invertible Architectures

gcl

List of Publications in Graph Contrastive Learning

generative-deep-learning-code-in-pytorch

The code repository for examples in the O'Reilly book 'Generative Deep Learning' using Pytorch

generative-models-for-molecules

Overview of published generative models that produce molecules

gflownets_tutorial

GflowNets, MCMC, Metropolis-Hasting, Gibbs sampling, Metropolis-adjusted Langevin, Inverse Transform Sampling, Acceptance-Rejection Method and Important Sampling

gnn-project

A Graph Neural Network project on HIV data

grafog

Graph Data Augmentation Library for PyTorch Geometric

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

graphcl_automated

[ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

graphormer

Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material discovery, drug discovery, etc.

gt4sd-core

GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process.

imbalancedmlc

An empirical analysis of the efficacy of several state-of-the-art methods on imbalanced Multilabel Classification datasets

imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).