Stars
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
Awesome Papers Using Vector Quantization for Recommender Systems (VQ4Rec)
AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games
[WWW'23] PyTorch implementation for "Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders".
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
The official GitHub page for the survey paper "A Survey of Large Language Models".
Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings".
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
Efficient and extensible GNNs enhanced recommender library based on RecBole.
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
An up-to-date, comprehensive and flexible recommendation library
A unified end-to-end machine intelligence platform
Pytorch domain library for recommendation systems
A unified, comprehensive and efficient recommendation library
【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容
Framework for evaluating ANNS algorithms on billion scale datasets.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
sentence embedding by Smooth Inverse Frequency weighting scheme
[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful