116 citations · 193 across the 15 of their papers we have counts for
5 papers · 1 filter
Data-Driven, ML-assisted Approaches to Problem Well-Posedness
Tom Bertalan, George A. Kevrekidis, Eleni D Koronaki +3
Classically, to solve differential equation problems, it is necessary to specify sufficient initial and/or boundary conditions so as to allow the existence of a unique solution. We…
Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information
Saurabh Malani, Tom S. Bertalan, Tianqi Cui +3
Experimental data is often comprised of variables measured independently, at different sampling rates (non-uniform t between successive measurements); and at a specific time poi…
Certified Invertibility in Neural Networks via Mixed-Integer Programming
Tianqi Cui, Thomas Bertalan, George J. Pappas +3
Neural networks are known to be vulnerable to adversarial attacks, which are small, imperceptible perturbations that can significantly alter the network's output. Conversely, there…
Transformations between deep neural networks
Tom Bertalan, Felix Dietrich, Ioannis G. Kevrekidis
We propose to test, and when possible establish, an equivalence between two different artificial neural networks by attempting to construct a data-driven transformation between the…
LOCA: LOcal Conformal Autoencoder for standardized data coordinates
Erez Peterfreund, Ofir Lindenbaum, Felix Dietrich +4
We propose a deep-learning based method for obtaining standardized data coordinates from scientific measurements.Data observations are modeled as samples from an unknown, non-linea…