Tsuda Lab.
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Kei Terayama
Researcher (RIKEN)
RIKEN
Latest
Bayesian optimization package: PHYSBO
Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring
De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning
Integrating Incompatible Assay Data Sets with Deep Preference Learning
Efficient Search for Energetically Favorable Molecular Conformations against Metastable States via Gray-Box Optimization
CrySPY: a crystal structure prediction tool accelerated by machine learning
Discovery of polymer electret material via de novo molecule generation and functional group enrichment analysis
Black-Box Optimization for Automated Discovery
Vision-based egg quality prediction in Pacific bluefin tuna (Thunnus orientalis) by deep neural network
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration
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