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ai2bmd

AI-powered ab initio biomolecular dynamics simulation

clifford-group-equivariant-simplicial-message-passing-networks

The implementation of the paper: Clifford Group Equivariant Simplicial Message Passing Networks @ ICLR2024

dl2_graph_tutorial

egnn

en_flows

fff

Free-form flows are a generative model training a pair of neural networks via maximum likelihood

geometric-algebra-transformer

geometric-gnn-dojo

Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks.

gvp

Geometric Vector Perceptron --- a rotation-equivariant GNN for learning from biomolecular structure

gvp-pytorch

Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure

lps

[NeurIPS'23 Spotlight] Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance (LPS), in PyTorch

mace

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

md17-baseline

A simple baseline for MD17 with a GNN conditioned on distance information.

midi

MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation

ponita

Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space.

steerable-e3-gnn

E(3) Steerable Graph Neural Network

uvadlc_notebooks

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022