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Kumo.AI
- Dortmund, Germany
- https://rusty1s.github.io
- @rusty1s
Stars
🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
[ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)
Python library assists deep learning on graphs
links to conference publications in graph-based deep learning
Benchmark datasets, data loaders, and evaluators for graph machine learning
A PyTorch Library for Accelerating 3D Deep Learning Research
Implementation of "Tracking without bells and whistles” and the multi-object tracking "Tracktor"
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
A research protocol for deep graph matching.
Metric Learning with Graph Convolutional Neural Networks
This is the code for ACL paper "Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network"
Must-read papers on entity alignment published in recent years
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
[ICLR 2019] Learning Representations of Sets through Optimized Permutations
KErnel OPerationS, on CPUs and GPUs, with autodiff and without memory overflows
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Deep Resource-Aware OpenCL Inference Networks
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Prettier is an opinionated code formatter.
Implementation of Graph Convolutional Networks in TensorFlow
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering