#Geometric-deep-learning
Showing 23 of 23 repositories tagged #geometric-deep-learning, ranked by stars
Graph Neural Network Library for PyTorch
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
StellarGraph - Machine Learning on Graphs
Convolutional Neural Network for 3D meshes in PyTorch
A library for differentiable robotics on manifolds.
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
Protein Graph Library
Python package for graph neural networks in chemistry and biology
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
TypeDB-ML is the Machine Learning integrations library for TypeDB
Equivariant Steerable CNNs Library for Pytorch https://quva-lab.github.io/escnn/
Relation-Shape Convolutional Neural Network for Point Cloud Analysis (CVPR 2019 Oral & Best paper finalist)
Low-Level Graph Neural Network Operators for PyG
Efficient and Modular ML on Temporal Graphs
Multi-language library for the calculation of spherical harmonics in Cartesian coordinates
Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called simplicial complexes.
The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"
Implementation of ICLR23 paper "Molecule Generation for Target Protein Binding with Structural Motifs"
Library to make any existing neural network architecture equivariant
A large-scale database for graph representation learning
Official repository for "PoissonNet: A Local-Global Approach for Learning on Surfaces"
A Python library for end-to-end learning on surfaces. It implements pre-processing functions that include geodesic algorithms, neural network layers that operate on surfaces, visualization tools and benchmarking functionalities.
Target-aware Variational Auto-encoders for Ligand Generation with Multimodal Protein Representation Learning