ffeng1996

ffeng1996's Stars

• google-deepmind/deepmind-research

  This repository contains implementations and illustrative code to accompany DeepMind publications

  Language:Jupyter Notebook13.1k3253212.6k

• uber/causalml

  Uplift modeling and causal inference with machine learning algorithms

  Language:Python5k84393767

• huawei-noah/HEBO

  Bayesian optimisation & Reinforcement Learning library developped by Huawei Noah's Ark Lab

  Language:Jupyter Notebook3.2k34048578

• vsitzmann/awesome-implicit-representations

  A curated list of resources on implicit neural representations.

  2.4k1140135

• google/neural-tangents

  Fast and Easy Infinite Neural Networks in Python

  Language:Jupyter Notebook2.3k63155225

• astooke/rlpyt

  Reinforcement Learning in PyTorch

  Language:Python2.2k52169322

• microsoft/Graphormer

  Graphormer is a general-purpose deep learning backbone for molecular modeling.

  Language:Python2.1k31151333

• ermongroup/cs228-notes

  Course notes for CS228: Probabilistic Graphical Models.

  Language:SCSS1.9k7029471

• rlworkgroup/garage

  A toolkit for reproducible reinforcement learning research.

  Language:Python1.9k561k310

• yfzhang114/Generalization-Causality

  关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

  1.1k481103

• nv-tlabs/ASE

  Language:Python7542175122

• weijiaheng/Advances-in-Label-Noise-Learning

  A curated (most recent) list of resources for Learning with Noisy Labels

  66014159

• jvpoulos/causal-ml

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

  657270124

• dengjianyuan/Survey_AI_Drug_Discovery

  30420164

• NVlabs/DiffRL

  [ICLR 2022] Accelerated Policy Learning with Parallel Differentiable Simulation

  Language:Python25191440

• loeweX/AmortizedCausalDiscovery

  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

  Language:Python1987841

• iancovert/Neural-GC

  Granger causality discovery for neural networks.

  Language:Python19531149

• huggingface/simulate

  🎢 Creating and sharing simulation environments for embodied and synthetic data research

  Language:Python1873812513

• DeepGraphLearning/ConfGF

  Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).

  Language:Python15910935

• microsoft/FS-Mol

  FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.

  Language:Python15712924

• facebookresearch/denoised_mdp

  Open source code for paper "Denoised MDPs: Learning World Models Better Than the World Itself"

  Language:Python1331361311

• Wuyxin/DIR-GNN

  Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

  Language:Python11551516

• vios-s/Diff-SCM

  Code for Diff-SCM paper

  Language:Python883011

• awarelab/continual_world

  Language:Python813616

• microsoft/csuite

  CSuite: A Suite of Benchmark Datasets for Causality

  Language:TeX55726

• ysharma1126/ssl_identifiability

  Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style

  Language:Python47246

• facebookresearch/entity-factored-rl

  Source code for the paper "Policy Architectures for Compositional Generalization in Control"

  Language:Python29843

• lgresele/independent-mechanism-analysis

  Code for the paper: "Independent mechanism analysis, a new concept?"

  Language:Jupyter Notebook25215

• WonderSeven/LSSAE

  The official implementation of paper "Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder"

  Language:Python24336

• mhw32/meta-inference-public

  A PyTorch implementation of "Meta-Amortized Variational Inference and Learning" (https://arxiv.org/abs/1902.01950)

  Language:Python14402