50 citations · 66 across the 6 of their papers we have counts for
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cs.LG2022★ 1 cited
Biases in In Silico Evaluation of Molecular Optimization Methods and Bias-Reduced Evaluation Methodology
Hiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami
We are interested in in silico evaluation methodology for molecular optimization methods. Given a sample of molecules and their properties of our interest, we wish not only to trai…
cs.LG2019★ 5 cited
Towards Stable Symbol Grounding with Zero-Suppressed State AutoEncoder
Masataro Asai, Hiroshi Kajino
While classical planning has been an active branch of AI, its applicability is limited to the tasks precisely modeled by humans. Fully automated high-level agents should be instead…
cs.LG2018★ 50 cited
Molecular Hypergraph Grammar with its Application to Molecular Optimization
Hiroshi Kajino
Molecular optimization aims to discover novel molecules with desirable properties. Two fundamental challenges are: (i) it is not trivial to generate valid molecules in a controllab…