Shunya Minami

National Institutes for Quantum and Radiological Science and Technology — Japan

Computer Science · Physical Sciences

3h-index71citations13works1.02yr avg
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Research Topics

Quantum Computing Algorithms and Architecture(4), Machine Learning in Materials Science(4), Domain Adaptation and Few-Shot Learning(3), Machine Learning and Data Classification(2), Machine Learning and ELM(2)

Publications13 total

QuantumBench: A Benchmark for Quantum Problem Solving
arXiv (Cornell University)·2025Open Access
QCoder Benchmark: Bridging Language Generation and Quantum Hardware through Simulator-Based Feedback
arXiv (Cornell University)·2025Open Access
Author response for "Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver"
2025
Author response for "Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver"
2025
Author Correction: Scaling Law of Sim2Real transfer learning in expanding computational materials databases for real-world predictions
npj Computational Materials·2025Open Access
Scaling law of Sim2Real transfer learning in expanding computational materials databases for real-world predictions
npj Computational Materials·2025· 5 citedOpen Access
Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver
arXiv (Cornell University)·2025· 1 citedOpen Access
Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver
Digital Discovery·2025· 1 citedOpen Access
Scaling Law of Sim2Real Transfer Learning in Expanding Computational Materials Databases for Real-World Predictions
arXiv (Cornell University)·2024· 2 citedOpen Access
Multitask Machine Learning to Predict Polymer–Solvent Miscibility Using Flory–Huggins Interaction Parameters
Macromolecules·2023· 56 citedOpen Access
Transfer learning with affine model transformation
arXiv (Cornell University)·2022Open Access
A General Class of Transfer Learning Regression without Implementation Cost
Proceedings of the AAAI Conference on Artificial Intelligence·2021· 4 citedOpen Access
A General Class of Transfer Learning Regression without Implementation Cost
arXiv (Cornell University)·2020· 2 citedOpen Access

Frequent Co-authors

Kenji Fukumizu(6), Yohichi Suzuki(6), Tadashi Kadowaki(6), Ryo Yoshida(5), Stephen Wu(4), Kazuya Shiratori(4), Kouhei Nakaji(4), Alán Aspuru‐Guzik(4), Yoshihiro Hayashi(3), Hiroki Sugisawa(3), Masashi Ishii(3), Isao Kuwajima(3), Yasuhiko Hayashi(2), Ryo Yoshida(2), Tatsuya Ishigaki(2), Taku Mikuriya(2), Hiroya Takamura(2), Yuuta Aoki(1), Teruki Tsurimoto(1), Okubo Tadamichi(1)