The similarity score for spectral comparison

Tandem Mass Spectrum Prediction with Graph Transformers

FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluati…

A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)

Geometry Sharing Network for 3D Point Cloud Classification and Segmentation

Relation-Shape Convolutional Neural Network for Point Cloud Analysis (CVPR 2019 Oral & Best paper finalist)

Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.

Python package for efficient mass spectrometry data processing and visualization

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

[ICLR 2022 poster] Official PyTorch implementation of "Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework"

pre-training BERT with molecular data

Convolutional nets which can take molecular graphs of arbitrary size as input.

OpenMM is a toolkit for molecular simulation using high performance GPU code.

Mass Spectrometry for Small Molecules using Deep Learning

Code for rendering the point cloud figures in paper: "PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows"

Pre-training Molecular Graph Representation with 3D Geometry, ICLR'22 (https://openreview.net/forum?id=xQUe1pOKPam)

GEOM: Energy-annotated molecular conformations

cG-SchNet - a conditional generative neural network for 3d molecular structures

SchNetPack - Deep Neural Networks for Atomistic Systems

Official implementation of pre-training via denoising for TorchMD-NET

N-Gram Graph: Simple Unsupervised Representation for Graphs, NeurIPS'19 (https://arxiv.org/abs/1806.09206)

DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules…

Public Implementation of ChIRo from "Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations"

Robust representation of semantically constrained graphs, in particular for molecules in chemistry

ATOM3D: tasks on molecules in three dimensions

GearNet and Geometric Pretraining Methods for Protein Structure Representation Learning, ICLR'2023 (https://arxiv.org/abs/2203.06125)

GeoSSL: Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching, ICLR'23 (https://openreview.net/forum?id=CjTHVo1dvR)