32 citations · 37 across the 7 of their papers we have counts for
Showing 2020 · cs.LGShow all
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cs.LG2020
Data-based Discovery of Governing Equations
Waad Subber, Piyush Pandita, Sayan Ghosh +3
Most common mechanistic models are traditionally presented in mathematical forms to explain a given physical phenomenon. Machine learning algorithms, on the other hand, provide a m…
cs.LG2020★ 3 cited
Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data
Steven Atkinson
What do data tell us about physics-and what don't they tell us? There has been a surge of interest in using machine learning models to discover governing physical laws such as diff…
cs.LG2020
Bayesian task embedding for few-shot Bayesian optimization
Steven Atkinson, Sayan Ghosh, Natarajan Chennimalai-Kumar +2
We describe a method for Bayesian optimization by which one may incorporate data from multiple systems whose quantitative interrelationships are unknown a priori. All general (nonr…