19 citations · 19 across the 7 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Symbolic Neural ODEs: Learning interpretable models from time-series data
Nibodh Boddupalli, Jeff Moehlis
We present a machine learning framework for identifying sparse, interpretable models of dynamical systems directly from time-series data. Our approach parameterizes the underlying…
cs.LG2024
Expressive Symbolic Regression for Interpretable Models of Discrete-Time Dynamical Systems
Adarsh Iyer, Nibodh Boddupalli, Jeff Moehlis
Interpretable mathematical expressions defining discrete-time dynamical systems (iterated maps) can model many phenomena of scientific interest, enabling a deeper understanding of…