weihua916

powerful-gnns

How Powerful are Graph Neural Networks?

imsat

Reproducing code for the paper "Learning Discrete Representations via Information Maximizing Self-Augmented Training"

LCTM

Implementation of a Latent Concept Topic Model (LCTM).

benchmarking-gnns

Repository for benchmarking graph neural networks

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dec

Gaius.jl

Divide and Conquer Linear Algebra

grlearning.github.io

Graph Representation Learning

jekyll-doc-theme

Jekyll theme for creating project documentation websites

jekyll-materialize-starter-template

Jekyll Materialize Starter Theme

KGNN-LS

A tensorflow implementation of Knowledge-aware Graph Neural Networks with Label Smoothness regularization

markdown-content

Markdown content for the www.aerobatic.io website

metaworld

An open source robotics benchmark for meta- and multi-task reinforcement learning

PGL

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

pytorch-meta

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

pytorch_geometric

Geometric Deep Learning Extension Library for PyTorch

SQuAD-explorer

Visually Explore the Stanford Question Answering Dataset

weihua916.github.io