Zhang, Wang, Weng, Tsui-Wei, Das, Subhro, Megretski, Alexandre, Daniel, Luca, and Nguyen, Lam M. ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. Retrieved from https://par.nsf.gov/biblio/10459929. Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023 .

Zhang, Wang, Weng, Tsui-Wei, Das, Subhro, Megretski, Alexandre, Daniel, Luca, & Nguyen, Lam M. ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023, (). Retrieved from https://par.nsf.gov/biblio/10459929.

Zhang, Wang, Weng, Tsui-Wei, Das, Subhro, Megretski, Alexandre, Daniel, Luca, and Nguyen, Lam M. "ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction". Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023 (). Country unknown/Code not available. https://par.nsf.gov/biblio/10459929.

@article{osti_10459929,
place = {Country unknown/Code not available}, title = {ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction}, url = {https://par.nsf.gov/biblio/10459929}, abstractNote = {}, journal = {Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023}, author = {Zhang, Wang and Weng, Tsui-Wei and Das, Subhro and Megretski, Alexandre and Daniel, Luca and Nguyen, Lam M.}, }