Steerable convolutions
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Updated
Aug 17, 2024 - Julia
Steerable convolutions
A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Code for "Effect of equivariance on training dynamics"
[GRaM at ICML'24] The Price of Freedom: Exploring Tradeoffs between Expressivity and Computational Efficiency in Equivariant Tensor Products
Library to make any existing neural network architecture equivariant
A Euclidean diffusion model for structure-based drug design.
[ICLR 2022] The implementation for the paper "Equivariant Graph Mechanics Networks with Constraints".
Equivariant Steerable CNNs Library for Pytorch https://quva-lab.github.io/escnn/
Continuous regular group convolutions for Pytorch
Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023
Implementation of E(n)-Transformer, which incorporates attention mechanisms into Welling's E(n)-Equivariant Graph Neural Network
Official PyTorch implementation of Möbius Convolutions for Spherical CNNs [SIGGRAPH 2022].
Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks.
Compute Lyapunov exponents and Covariant-Lyapunov-Vectors of an RNN update trajectory
ImageNet1k-pretrained SE(2) Equivariant Vision Models
DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design
[NeurIPS'23 Spotlight] Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance (LPS), in PyTorch
[NAACL 2022] Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning.
Implementation of Group-Convolutions as Keras layers.
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