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ab-initio-thermodynamics-of-water

“Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti

aenet

Atomic interaction potentials based on artificial neural networks

ai4pfas

Dataset and code for "Uncertainty-Informed Deep Transfer Learning of PFAS Toxicity"

artificial-intelligence-for-predicting-materials-properties

asap

ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-tips

b3db

A large benchmark dataset, Blood-Brain Barrier Database (B3DB), complied from 50 published resources.

bcdb

Block Copolymer Phase Behavior Database

bocs

Bottom-up Open-source Coarse-graining Software

chemical_vae

Code for 10.1021/acscentsci.7b00572, now running on Keras 2.0 and Tensorflow

chemprop

Message Passing Neural Networks for Molecule Property Prediction

coarse-graining-auto-encoders

confgf

Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).

copolymer_informatics

Code for the paper Copolymer Informatics with Multi-Task Deep Neural Networks

csg

coarse-graining module

csg-tutorials

VOTCA-CSG coarse-graining tutorials

curated-cofs

Clean, Uniform and Refined with Automatic Tracking from Experimental Database (CURATED) COFs

dag-gnn

de_novo_design_rnn

Code for "De novo molecular design with chemical language models"

dispersant_screening_pal

dtnn

Deep Tensor Neural Network

dynim

Dynamic Importance Sampling

enn

eunomia

Chemist AI Agent for Developing Materials Datasets with Natural Language Prompts

exmol

Explainer for black box models that predict molecule properties

fast

Fusion models for Atomic and molecular STructures (FAST)

featurization

g-schnet

G-SchNet - a generative model for 3d molecular structures

ga

Code for the paper: Augmenting genetic algorithms with deep neural networks for exploring the chemical space