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Code and models for the paper "One Transformer Fits All Distributions in Multi-Modal Diffusion"
Best Practices on Recommendation Systems
RecSys 2022 Tutorial Hands on Explainable Recommender Systems with Knowledge Graphs
Recommender Systems Paperlist that I am interested in
😱 从源码层面,剖析挖掘互联网行业主流技术的底层实现原理,为广大开发者 “提升技术深度” 提供便利。目前开放 Spring 全家桶,Mybatis、Netty、Dubbo 框架,及 Redis、Tomcat 中间件等
Recommendation Algorithm大规模推荐算法库,包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM,DSIN,SIGN,IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESM…
The source code for "Global Context Enhanced Graph Neural Network for Session-based Recommendation".
A unified, comprehensive and efficient recommendation library
This is the official code for WWW 2021 paper "Session-aware Linear Item-Item Models for Session-based Recommendation"
Code for the WWW'21 paper "HGCF: Hyperbolic Graph Convolution Networks for Collaborative Filtering"
PyTorch Tutorial for Deep Learning Researchers
This is our implementation of GHCF: Graph Heterogeneous Collaborative Filtering (AAAI 2021)
The paper author has released the source code as following https://github.com/CCIIPLab/GCE-GNN
Must-read papers on graph neural networks (GNN)
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A Collaborative Session-based Recommendation Approach with Parallel Memory Modules, SIGIR 2019
This is our implementation of EHCF: Efficient Heterogeneous Collaborative Filtering (AAAI 2020)
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial…
Download and preprocess popular sequential recommendation datasets
A comprehensive collection of recent papers on graph deep learning
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization (NAACL 2019)
Classic papers and resources on recommendation
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems