Learning interaction rules from multi-animal trajectories via augmented behavioral models

Keisuke Fujii 0001, Naoya Takeishi, Kazushi Tsutsui, Emyo Fujioka, Nozomi Nishiumi, Ryoya Tanaka, Mika Fukushiro, Kaoru Ide, Hiroyoshi Kohno, Ken Yoda, Susumu Takahashi, Shizuko Hiryu, Yoshinobu Kawahara. Learning interaction rules from multi-animal trajectories via augmented behavioral models. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 11108-11122, 2021. [doi]

@inproceedings{FujiiTTFNTFIKYT21,
  title = {Learning interaction rules from multi-animal trajectories via augmented behavioral models},
  author = {Keisuke Fujii 0001 and Naoya Takeishi and Kazushi Tsutsui and Emyo Fujioka and Nozomi Nishiumi and Ryoya Tanaka and Mika Fukushiro and Kaoru Ide and Hiroyoshi Kohno and Ken Yoda and Susumu Takahashi and Shizuko Hiryu and Yoshinobu Kawahara},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/5c572eca050594c7bc3c36e7e8ab9550-Abstract.html},
  researchr = {https://researchr.org/publication/FujiiTTFNTFIKYT21},
  cites = {0},
  citedby = {0},
  pages = {11108-11122},
  booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
  editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}