ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction

Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen. ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. In Andreas Krause 0001, Emma Brunskill, KyungHyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett, editors, International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA. Volume 202 of Proceedings of Machine Learning Research, pages 41694-41714, PMLR, 2023. [doi]

@inproceedings{ZhangWDMDN23,
  title = {ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction},
  author = {Wang Zhang and Tsui-Wei Weng and Subhro Das and Alexandre Megretski and Luca Daniel and Lam M. Nguyen},
  year = {2023},
  url = {https://proceedings.mlr.press/v202/zhang23ao.html},
  researchr = {https://researchr.org/publication/ZhangWDMDN23},
  cites = {0},
  citedby = {0},
  pages = {41694-41714},
  booktitle = {International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA},
  editor = {Andreas Krause 0001 and Emma Brunskill and KyungHyun Cho and Barbara Engelhardt and Sivan Sabato and Jonathan Scarlett},
  volume = {202},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}