Neuro-inspired quantum associative memory using adiabatic hamiltonian evolution. - Yoshihiro Osakabe; Shigeo Sato; Hisanao Akima; Masao Sakuraba; Mitsunaga Kinjo (IJCNN, 2017)

Quantum Associative Memory with Quantum Neural Network via Adiabatic Hamiltonian Evolution. - Yoshihiro Osakabe; Hisanao Akima; Masao Sakuraba; Mitsunaga Kinjo; Shigeo Sato (IEICE Trans. Inf. Syst., 2017)

Hitachi Materials Informatics Analytics Platform Assisting Rapid Development. - Yoshihiro Osakabe; Akinori Asahara; Hidekazu Morita (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1), 2020)

MatVAE: Independently Trained Nested Variational Autoencoder for Generating Chemical Structural Formula. - Yoshihiro Osakabe; Akinori Asahara (AAAI Spring Symposium: MLPS, 2021)

Learning Rule for a Quantum Neural Network Inspired by Hebbian Learning. - Yoshihiro Osakabe; Shigeo Sato; Hisanao Akima; Mitsunaga Kinjo; Masao Sakuraba (IEICE Trans. Inf. Syst., 2021)

Interactive Support System for Idea Divergence-Convergence Iteration. - Akinori Asahara; Yoshihiro Osakabe; Karin Tsuda; Hidekazu Morita (IEEE Big Data, 2022)

QUBO-inspired Molecular Fingerprint for Chemical Property Prediction. - Koichiro Yawata; Yoshihiro Osakabe; Takuya Okuyama; Akinori Asahara (IEEE Big Data, 2022)

QUBO Decision Tree: Annealing Machine Extends Decision Tree Splitting. - Koichiro Yawata; Yoshihiro Osakabe; Takuya Okuyama; Akinori Asahara (ICKG, 2022)

Proposing Novel High-Performance Compounds by Nested VAEs Trained Independently on Different Datasets. - Yoshihiro Osakabe; Akinori Asahara (IEA/AIE, 2022)

Proposing Novel Extrapolative Compounds by Nested Variational Autoencoders. - Yoshihiro Osakabe; Akinori Asahara (CoRR, 2023)

Variational Bayes Decomposition for Inverse Estimation with Superimposed Multispectral Intensity. - Akinori Asahara; Yoshihiro Osakabe; Yamamoto Mitsuya; Hidekazu Morita (CoRR, 2024)