ethanmock

ethanmock's Stars

• Significant-Gravitas/AutoGPT

  AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

  Language:Python168k1.5k2.8k44.3k

• CompVis/stable-diffusion

  A latent text-to-image diffusion model

  Language:Jupyter Notebook68.2k55871310.2k

• recommenders-team/recommenders

  Best Practices on Recommendation Systems

  Language:Python19.2k2738683.1k

• lixin4ever/Conference-Acceptance-Rate

  Acceptance rates for the major AI conferences

  Language:Jupyter Notebook4.2k12828298

• maziarraissi/PINNs

  Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

  Language:Python3.9k117551.3k

• hojonathanho/diffusion

  Denoising Diffusion Probabilistic Models

  Language:Python3.8k2021369

• RUCAIBox/RecBole

  A unified, comprehensive and efficient recommendation library

  Language:Python3.4k42977613

• HobbitLong/SupContrast

  PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

  Language:Python3.1k20135529

• kzl/decision-transformer

  Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

  Language:Python2.4k2964451

• WLiK/LLM4Rec-Awesome-Papers

  A list of awesome papers and resources of recommender system on large language model (LLM).

  1.3k228110

• rixwew/pytorch-fm

  Factorization Machine models in PyTorch

  Language:Python1k1638225

• RUCAIBox/Awesome-RSPapers

  Recommender System Papers

  941315145

• facebookresearch/generative-recommenders

  Repository hosting code used to reproduce results in "Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152).

  Language:Python7302448131

• PetarV-/DGI

  Deep Graph Infomax (https://arxiv.org/abs/1809.10341)

  Language:Python6301219135

• juho-lee/set_transformer

  Pytorch implementation of set transformer

  Language:Jupyter Notebook5441219103

• jannerm/trajectory-transformer

  Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"

  Language:Python46262065

• Linear95/CLUB

  Code for ICML2020 paper - CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information

  Language:Jupyter Notebook30872739

• westlake-repl/Recommendation-Systems-without-Explicit-ID-Features-A-Literature-Review

  Paper List of Pre-trained Foundation Recommender Models

  30610125

• nishnik/Deep-Semantic-Similarity-Model-PyTorch

  My PyTorch implementation of the Deep Semantic Similarity Model (DSSM)/Convolutional Latent Semantic Model (CLSM) described here: http://research.microsoft.com/pubs/226585/cikm2014_cdssm_final.pdf.

  Language:Python2128349

• xiangwang1223/disentangled_graph_collaborative_filtering

  Disentagnled Graph Collaborative Filtering, SIGIR2020

  Language:Python1325628

• intel/torch-ccl

  oneCCL Bindings for Pytorch*

  Language:C++85103724

• liyinxiao/UnifiedEmbeddingModel

  Implementation of unified embedding model from Embedding-based Retrieval in Facebook Search.

  Language:Python763015

• ruizhang-ai/GMCF_Neural_Graph_Matching_based_Collaborative_Filtering

  GMCF: Neural Graph Matching based Collaborative Filtering, SIGIR 2021

  Language:Python5421212

• ruizhang-ai/SIGN-Detecting-Beneficial-Feature-Interactions-for-Recommender-Systems

  Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021

  Language:Python33376

• thunlp/explore-and-evaluate

  Code for EMNLP2020 paper "Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment".

  Language:Python296107

• ruizhang-ai/HIRS-Detecting_Arbitrary_Order_Beneficial_Feature_Interactions_for_Recommender_Systems

  Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems, KDD 2022

  Language:Python23123

• DavyMorgan/dps

  data process service

  Language:Python12000

• wujcan/GCM

  Language:Python9237

• ljf012/GNN-DSR

  Language:Python8174

• alibaba/Dynamic-popularity-aware-recommendation

  Dynamic popularity-aware contrastive learning for recommendation

  Language:Jupyter Notebook7305