Deep Bayesian Active Learning for Accelerating Stochastic Simulation

Author:

Wu Dongxia1ORCID,Niu Ruijia1ORCID,Chinazzi Matteo2ORCID,Vespignani Alessandro2ORCID,Ma Yi-An1ORCID,Yu Rose1ORCID

Affiliation:

1. University of California, San Diego, La Jolla, CA, USA

2. Northeastern University, Boston, MA, USA

Funder

NSF (National Science Foundation)

Facebook

U.S. Department Of Energy

HHS/CDC

U. S. Army Research Office

Publisher

ACM

Reference56 articles.

1. Sercan Arik , Chun-Liang Li , Jinsung Yoon , Rajarishi Sinha , Arkady Epshteyn , Long Le , Vikas Menon , Shashank Singh , Leyou Zhang , Martin Nikoltchev , 2020 . Interpretable Sequence Learning for Covid-19 Forecasting . Advances in Neural Information Processing Systems , Vol. 33 (2020). Sercan Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, et al. 2020. Interpretable Sequence Learning for Covid-19 Forecasting. Advances in Neural Information Processing Systems, Vol. 33 (2020).

2. Søren Asmussen and Peter W Glynn . 2007. Stochastic simulation: algorithms and analysis . Vol. 57 . Springer Science & Business Media . Søren Asmussen and Peter W Glynn. 2007. Stochastic simulation: algorithms and analysis. Vol. 57. Springer Science & Business Media.

3. Salva Rühling Cachay Venkatesh Ramesh Jason N. S. Cole Howard Barker and David Rolnick. 2021. ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models. In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https://arxiv.org/abs/2111.14671 Salva Rühling Cachay Venkatesh Ramesh Jason N. S. Cole Howard Barker and David Rolnick. 2021. ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models. In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https://arxiv.org/abs/2111.14671

4. Kathryn Chaloner and Isabella Verdinelli. 1995. Bayesian experimental design: A review. Statist. Sci. (1995) 273--304. Kathryn Chaloner and Isabella Verdinelli. 1995. Bayesian experimental design: A review. Statist. Sci. (1995) 273--304.

5. Ricky TQ Chen , Yulia Rubanova , Jesse Bettencourt , and David Duvenaud . 2018 . Neural ordinary differential equations . In Proceedings of the 32nd International Conference on Neural Information Processing Systems. 6572--6583 . Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David Duvenaud. 2018. Neural ordinary differential equations. In Proceedings of the 32nd International Conference on Neural Information Processing Systems. 6572--6583.

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