Tsuda Laboratory

combo

COMmon Bayesian Optimization

ChemGE

Population-based De Novo Molecule Generation, Using Grammatical Evolution

MDTS

Materials Design by Monte Carlo Tree Search

combo3

COMBO for Python 3

BLOX

BoundLess Objective-free eXploration (BLOX) for discovery of out-of-trend materials

fmqa

A trainable Binary Quadratic Model (BQM) as a Factorization Machine (FM)

ACP4

AutoCorrelation of Pharmacophore Features

PDC

Efficient phase diagram construction based on uncertainty sampling

PepGAN

bVAE-IM

Implementation of "Chemical Design with GPU-based Ising Machine"

FL_ChemTS

molecule design for fluorescence

rxngenerator

A generative model for molecular generation via multi-step chemical reactions

NMR-TS

Molecule identifier from NMR spectrum using de novo molecule generator

SLEPA

Self-Learning Entropic Population Annealing

nightvision

bopp

Black-box optimization of peptides and proteins

GaussianRunPack

GaussianRunPack

MolSLEPA

Interpretable Fragment-based Molecule Design with Self-learning Entropic Population Annealing

ChemTS-torch

PyTorch Implementation of ChemTS as a de novo molecule designer

Polymer-degradability-ranking

Revealing Factors Influencing Polymer Degradation with Rank-based Machine Learning

PrefInt

Integrating Data via Preference Learning

PrefIntNN

DPDI package provides a neural network-based method of integrating data via learning pairwise relations.

DT-sampler

fast-stein-correction

Implementation of "Boltzmann sampling with quantum annealers via fast Stein correction"

conbqa

RIETAN-RPA

RPPF

Ranking of Pareto solutions based on projection free-energy

ALW_ChemTS

Parallelized ChemTS for the design of molecules that absorb light at long wavelengths

ab-predictor

test

DOPBO

Drainable One-Pot Bayesian Optimization