4 citations · 8 across the 5 of their papers we have counts for
5 papers
SynPAT: A System for Generating Synthetic Physical Theories with Data
Jonathan Lenchner, Karan Srivastava, Joao Goncalves +2
Machine-assisted methods for discovering physical laws from background theory and data have recently emerged, promising to advance our understanding of the physical world. However,…
Distributionally Robust Regularization of Sparse Integer Programming Trained Learning Models
Sanjeeb Dash, Soumyadip Ghosh, Joao Goncalves +1
Building explainable machine learning models is crucial for human users to be able to interpret the proposed statistical relationship obtained from the training data. Mixed-integer…
Bayesian Experimental Design for Symbolic Discovery
Kenneth L. Clarkson, Cristina Cornelio, Sanjeeb Dash +3
This study concerns the formulation and application of Bayesian optimal experimental design to symbolic discovery, which is the inference from observational data of predictive mode…
AI Descartes: Combining Data and Theory for Derivable Scientific Discovery
Cristina Cornelio, Sanjeeb Dash, Vernon Austel +6
Scientists have long aimed to discover meaningful formulae which accurately describe experimental data. A common approach is to manually create mathematical models of natural pheno…
Symbolic Regression using Mixed-Integer Nonlinear Optimization
Vernon Austel, Cristina Cornelio, Sanjeeb Dash +4
The Symbolic Regression (SR) problem, where the goal is to find a regression function that does not have a pre-specified form but is any function that can be composed of a list of…