[TPAMI 2024] Code for "ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting"

[TNNLS 2022] Code for "Learning Disentangled Graph Convolutional Networks Locally and Globally"

Code for ICLR 2023 paper (Oral) — Towards Stable Test-Time Adaptation in Dynamic Wild World

算法工程师-机器学习面试题总结

🐳 LeetCode 算法笔记：面试、刷题、学算法。在线阅读地址：https://datawhalechina.github.io/leetcode-notes/

⛽️「算法通关手册」：超详细的「算法与数据结构」基础讲解教程，从零基础开始学习算法知识，850+ 道「LeetCode 题目」详细解析，200 道「大厂面试热门题目」。

Tensors and Dynamic neural networks in Python with strong GPU acceleration

A more expressive and most importantly, more efficient system for distributed data analytics.

Temporal Graph Benchmark project repo

Official repository for AAAI2024 paper <Unraveling Batch Normalization for Realistic Test-Time Adaptation>.

MaSIF- Molecular surface interaction fingerprints. Geometric deep learning to decipher patterns in molecular surfaces.

Collection of awesome test-time (domain/batch/instance) adaptation methods

Un-mixing Test-time Normalization Statistics: Combatting Label Temporal Correlation

StructureNet: Hierarchical Graph Networks for 3D Shape Generation

ICLR 2023 Paper submission analysis from https://openreview.net/group?id=ICLR.cc/2023/Conference

[ICLR 2024] ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation

A Newtonian message passing network for deep learning of interatomic potentials and forces

Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings".

[WWW 2023] Code for "Graph Neural Networks with Diverse Spectral Filtering"

The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs"

Code for "SaliencyCut: Augmenting Plausible Anomalies for Anomaly Detection"

[AAAI 2023] Official PyTorch implementation of the paper "SLAug: Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation"

Source code of NeurIPS 2022 paper *A Variational Edge Partition Model for Supervised Graph Representation Learning*

Implementation of 'Exploring edge disentanglement for node classification', published in WWW2022

NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure

A tensorflow implementation of GCN-LPA

A Pytorch implementation of GCN-LPA

A curated collection of papers, tutorials, videos, and other valuable resources related to Mamba.