Tsuda Laboratory

Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo

Kashiwa, Japan

Pinned Repositories

ACP4
AutoCorrelation of Pharmacophore Features
Language:OCaml15 1 02
BLOX
BoundLess Objective-free eXploration (BLOX) for discovery of out-of-trend materials
Language:Python23 5 06
ChemGE
Population-based De Novo Molecule Generation, Using Grammatical Evolution
Language:Python40 12 1411
ChemTS
Molecule Design using Monte Carlo Tree Search with Neural Rollout
Language:Python160 20 1252
combo
COMmon Bayesian Optimization
Language:Python151 14 1037
combo3
COMBO for Python 3
Language:Python33 11 215
DP-ChemTS
A distributed framework based on Monte Carlo tree search for accelerating molecular discovery.
Language:Python14 8 03
fmqa
A trainable Binary Quadratic Model (BQM) as a Factorization Machine (FM)
Language:Python23 10 55
MDTS
Materials Design by Monte Carlo Tree Search
Language:Python34 10 010
PDC
Efficient phase diagram construction based on uncertainty sampling
Language:Jupyter Notebook14 10 07

Tsuda Laboratory's Repositories

tsudalab/combo
COMmon Bayesian Optimization
Language:Python151 14 1037
tsudalab/ChemGE
Population-based De Novo Molecule Generation, Using Grammatical Evolution
Language:Python40 12 1411
tsudalab/MDTS
Materials Design by Monte Carlo Tree Search
Language:Python34 10 010
tsudalab/combo3
COMBO for Python 3
Language:Python33 11 215
tsudalab/fmqa
A trainable Binary Quadratic Model (BQM) as a Factorization Machine (FM)
Language:Python23 10 55
tsudalab/ACP4
AutoCorrelation of Pharmacophore Features
Language:OCaml15 1 02
tsudalab/PDC
Efficient phase diagram construction based on uncertainty sampling
Language:Jupyter Notebook14 10 07
tsudalab/PepGAN
Language:Python13 2 05
tsudalab/rxngenerator
A generative model for molecular generation via multi-step chemical reactions
Language:Python12 9 13
tsudalab/bVAE-IM
Implementation of "Chemical Design with GPU-based Ising Machine"
Language:Python11 8 03
tsudalab/FL_ChemTS
molecule design for fluorescence
Language:Python11 8 06
tsudalab/SLEPA
Self-Learning Entropic Population Annealing
Language:Python8 8 12
tsudalab/nightvision
Language:Python7 10 13
tsudalab/bopp
Black-box optimization of peptides and proteins
Language:Python6 3 03
tsudalab/GaussianRunPack
GaussianRunPack
Language:Python6 8 01
tsudalab/Polymer-degradability-ranking
Revealing Factors Influencing Polymer Degradation with Rank-based Machine Learning
Language:Python6 7 00
tsudalab/MolSLEPA
Interpretable Fragment-based Molecule Design with Self-learning Entropic Population Annealing
Language:Python5 8 01
tsudalab/ChemTS-torch
PyTorch Implementation of ChemTS as a de novo molecule designer
Language:Python4 2 01
tsudalab/PrefInt
Integrating Data via Preference Learning
Language:Python4 10 02
tsudalab/PrefIntNN
DPDI package provides a neural network-based method of integrating data via learning pairwise relations.
Language:Jupyter Notebook4 8 01
tsudalab/DT-sampler
Language:Python3 8 0
tsudalab/conbqa
Language:Python2 8 0
tsudalab/fast-stein-correction
Implementation of "Boltzmann sampling with quantum annealers via fast Stein correction"
Language:Jupyter Notebook2 9 01
tsudalab/RIETAN-RPA
Language:Python2 7 00
tsudalab/ALW_ChemTS
Parallelized ChemTS for the design of molecules that absorb light at long wavelengths
Language:Python1 8 0
tsudalab/POPSL
A PSL-based multi-objective optimization algorithm
Language:Python1 8 0
tsudalab/RPPF
Ranking of Pareto solutions based on projection free-energy
Language:Python1 8 00
tsudalab/ab-predictor
test
Language:Python1 0
tsudalab/brxngenerator
A binary-version of rxngenerator
Language:Python
tsudalab/DOPBO
Drainable One-Pot Bayesian Optimization
Language:Python8 0