42 citations · 77 across the 6 of their papers we have counts for
6 papers
From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models
Zehao Li, Yasuhiro Yoshikai, Shumpei Nemoto +2
Understanding how chemical language models (CLMs) learn chemical meaning from molecular string representations, rather than only surface-level string patterns, is an important ques…
Molecular notation can act as a shortcut in AI benchmark evaluation
Yosuke Kikuchi, Yasuhiro Yoshikai, Shumpei Nemoto +4
High predictive accuracy does not necessarily mean that an AI model relies on information relevant to its scientific task. Molecular prediction illustrates this concern: the same m…
A novel molecule generative model of VAE combined with Transformer for unseen structure generation
Yasuhiro Yoshikai, Tadahaya Mizuno, Shumpei Nemoto +1
Recently, molecule generation using deep learning has been actively investigated in drug discovery. In this field, Transformer and VAE are widely used as powerful models, but they…
Difficulty in chirality recognition for Transformer architectures learning chemical structures from string
Yasuhiro Yoshikai, Tadahaya Mizuno, Shumpei Nemoto +1
Recent years have seen rapid development of descriptor generation based on representation learning of extremely diverse molecules, especially those that apply natural language proc…
Investigation of chemical structure recognition by encoder-decoder models in learning progress
Shumpei Nemoto, Tadahaya Mizuno, Hiroyuki Kusuhara
Descriptor generation methods using latent representations of encoderdecoder (ED) models with SMILES as input are useful because of the continuity of descriptor and restorabilit…
Investigation of a Data Split Strategy Involving the Time Axis in Adverse Event Prediction Using Machine Learning
Katsuhisa Morita, Tadahaya Mizuno, Hiroyuki Kusuhara
Adverse events are a serious issue in drug development and many prediction methods using machine learning have been developed. The random split cross-validation is the de facto sta…