Code and material necessary for the reproduction of the results in the paper "Application of deep metric learning to molecular similarity".

An end-to-end tool for synthesis planning

AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

An awesome README template to jumpstart your projects!

ELKI Data Mining Toolkit

GraphXAI: Resource to support the development and evaluation of GNN explainers

Plugin to show molecule images on mouseover using RDKit and Altair

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

Distributed Evolutionary Algorithms in Python

Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning

LillyMol Public Code

Gaussian mixture models in PyTorch.

Machine learning accelerated docking screens

A Python Library for Evaluating the Reliability of Dimensionality Reduction Embeddings

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

Geometric Latent Diffusion Models for 3D Molecule Generation

Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).

Dr. Alexey Orlov's personal website.

Official code of "Towards Multi-Grained Explainability for Graph Neural Networks" (NeurIPS 2021) + Pytorch Implementation of recent attribution methods for GNNs

A beautiful, simple, clean, and responsive Jekyll theme for academics

MultiMAE: Multi-modal Multi-task Masked Autoencoders, ECCV 2022

AutoDock Vina