| Lineage EM algorithm for inferring latent states from cellular lineage trees S Nakashima, Y Sughiyama, TJ Kobayashi Bioinformatics 36 (9), 2829-2838, 2020 | 12 | 2020 |
| Fitness response relation of a multitype age-structured population dynamics Y Sughiyama, S Nakashima, TJ Kobayashi Physical Review E 99 (1), 012413, 2019 | 9 | 2019 |
| Subspace selection via DR-submodular maximization on lattices S Nakashima, T Maehara Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4618-4625, 2019 | 7 | 2019 |
| A compact representation for modular semilattices and its applications H Hirai, S Nakashima Order 37 (3), 479-507, 2020 | 4 | 2020 |
| Acceleration of evolutionary processes by learning and extended Fisher's fundamental theorem S Nakashima, TJ Kobayashi Physical Review Research 4 (1), 013069, 2022 | 3 | 2022 |
| Multiple knapsack-constrained monotone DR-submodular maximization on distributive lattice: —Continuous Greedy Algorithm on Median Complex— T Maehara, S Nakashima, Y Yamaguchi Mathematical Programming 194 (1), 85-119, 2022 | 1 | 2022 |
| Rank axiom of modular supermatroids: A connection with directional DR submodular functions T Maehara, S Nakashima Advances in Applied Mathematics 134, 102304, 2022 | 1 | 2022 |
| Population dynamics models for various forms of adaptation S Nakashima, TJ Kobayashi Biophysics and Physicobiology 20 (3), e200034, 2023 | | 2023 |
| Mathematical Structure of Coordination between Individual Learning and Populational Evolution and its Applications S Nakashima University of Tokyo, 2021 | | 2021 |
| Pathwise analysis for a structured population dynamics and its application to inference of cell states Y Sughiyama, S Nakashima, TJ Kobayashi StatPhys 27 Main Conference, 2019 | | 2019 |
Tetsuya J. KobayashiInstitute of Industrial Science, the University of TokyoBestätigte E-Mail-Adresse bei mail.crmind.net
