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PyTorch extensions for high performance and large scale training.
Agentic components of the Llama Stack APIs
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
A unified, comprehensive and efficient recommendation library
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
PyTorch implementations of deep reinforcement learning algorithms and environments
Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Model interpretability and understanding for PyTorch
🤖 A Python library for learning and evaluating knowledge graph embeddings
Benchmark datasets, data loaders, and evaluators for graph machine learning
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
Pytorch Geometric Tutorials
High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
Graph Neural Networks with Keras and Tensorflow 2.
Neural Graph Collaborative Filtering, SIGIR2019
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
Must-read papers on graph neural networks (GNN)
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
Graph Neural Network Library for PyTorch
Repository for benchmarking graph neural networks
Python package built to ease deep learning on graph, on top of existing DL frameworks.