geometric-deep-learning topic

NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN framework

SitaoLuan

The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"

qitianwu

[CVPR'22] Parametric Scattering Networks

bentherien

Lign (/lignə/): Extension to PyTorch for graphs and geometric deep learning

wzjoriv

A Transformer made of Rotation-equivariant Attention using Vector Neurons

lucidrains

We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.

Thinklab-SJTU

A geometric deep learning pipeline for predicting protein interface contacts. (ICLR 2022)

BioinfoMachineLearning

Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called simplicial complexes.

stefaniaebli

Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG

rkobler

List of Geometric GNNs for 3D atomic systems

AlexDuvalinho