Stars
Tensors and Dynamic neural networks in Python with strong GPU acceleration
🤗 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.
🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
A PyTorch Library for Accelerating 3D Deep Learning Research
Prettier is an opinionated code formatter.
🔬 MCP server to query KumoRFM in your agentic flows
This repository is for tracking issues, feature requests, and feedback for KumoRFM.
A research protocol for deep graph matching.
KErnel OPerationS, on CPUs and GPUs, with autodiff and without memory overflows
links to conference publications in graph-based deep learning
Python library assists deep learning on graphs
Benchmark datasets, data loaders, and evaluators for graph machine learning
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Must-read papers on entity alignment published in recent years
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
Implementation of Graph Convolutional Networks in TensorFlow
Implementation of "Tracking without bells and whistles” and the multi-object tracking "Tracktor"
[ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)
Graph Classification with Graph Convolutional Networks in PyTorch [NeurIPS 2018 Workshop]
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
This is the code for ACL paper "Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network"
[ICLR 2019] Learning Representations of Sets through Optimized Permutations
Deep Resource-Aware OpenCL Inference Networks
Metric Learning with Graph Convolutional Neural Networks