32 citations · 32 across the 3 of their papers we have counts for
3 papers
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…
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…
Data-driven discovery of free-form governing differential equations
Steven Atkinson, Waad Subber, Liping Wang +3
We present a method of discovering governing differential equations from data without the need to specify a priori the terms to appear in the equation. The input to our method is a…