Deep neural networks for density functional theory Hamiltonian.
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Updated
May 22, 2024 - Python
Deep neural networks for density functional theory Hamiltonian.
Complex-based Ligand-Binding Proteins Redesign by Equivariant Diffusion-based Generative Models
[AAAI 2023] The implementation for the paper "Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs"
It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR) in 2024.
[NAACL 2022] Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning.
Dock2D: Synthetic datasets for the molecular recognition problem
ARES implement in PyTorch
[ICLR 2024 Spotlight] Official Implementation of "Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products"
[ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
The official source code for Task-Equivariant Graph Few-shot Learning (TEG) at KDD 2023.
Official implementation of the NeurIPS 23 spotlight paper of ♾️InfGCN♾️.
E(2)-Equivariant CNNs Library for Pytorch
[NeurIPS 2022] The implementation for the paper "Equivariant Graph Hierarchy-Based Neural Networks".
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
Extended DeepH (xDeepH) method for magnetic materials.
A 3D-equivariant neural network for protein structure accuracy estimation
Implementing SE(3)-equivariant neural networks with Flux.jl
A project that seeks to code ud the boardgame hive and train a neural network to play it
PENN code for NeurIPS 2022
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