Research theme for competitive and other funds (6):
2024 - 2028 トポロジカル制御理論の確立
2022 - 2027 Foundation of "Machine Learning Physics" --- Revolutionary Transformation of Fundame ntal Physics by A New Field Integrating Machine Learning and Physics
2022 - 2027 Approach from topological geometry toward machine learning
2024 - 2026 ネットワーク・トポロジーを利用した生化学反応系のロバスト制御解析
2020 - 2023 Symmetry principles for novel quantum phases
2011 - 2013 非可換渦のダイナミクスとその高密度QCD物質への応用
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Papers (42):
Koji Hashimoto, Yuji Hirono, Jun Maeda, Jojiro Totsuka-Yoshinaka. Neural network representation of quantum systems. Machine Learning: Science and Technology. 2024. 5. 4. 045039-045039
Yuji Hirono, Akinori Tanaka, Kenji Fukushima. Understanding Diffusion Models by Feynman's Path Integral. Proceedings of the 41st International Conference on Machine Learning (ICML). 2024
Koji Hashimoto, Yuji Hirono, Akiyoshi Sannai. Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE. Machine Learning: Science and Technology. 2024
Lata Thakur, Yuji Hirono. Quarkonium spectral functions in a bulk viscous quark-gluon plasma. IL NUOVO CIMENTO C. 2024. 47
Yuji Hirono, Minyoung You, Stephen Angus, Gil Young Cho. A symmetry principle for gauge theories with fractons. SciPost Physics. 2024. 16. 2