23 citations · 47 across the 5 of their papers we have counts for
6 papers
Recurrent Neural Networks in the Eye of Differential Equations
Murphy Yuezhen Niu, Lior Horesh, Isaac Chuang
To understand the fundamental trade-offs between training stability, temporal dynamics and architectural complexity of recurrent neural networks~(RNNs), we directly analyze RNN arc…
Globally Optimal Symbolic Regression
Vernon Austel, Sanjeeb Dash, Oktay Gunluk +4
In this study we introduce a new technique for symbolic regression that guarantees global optimality. This is achieved by formulating a mixed integer non-linear program (MINLP) who…
Should You Derive, Or Let the Data Drive? An Optimization Framework for Hybrid First-Principles Data-Driven Modeling
Remi R. Lam, Lior Horesh, Haim Avron +1
Mathematical models are used extensively for diverse tasks including analysis, optimization, and decision making. Frequently, those models are principled but imperfect representati…
Image classification using local tensor singular value decompositions
Elizabeth Newman, Misha Kilmer, Lior Horesh
From linear classifiers to neural networks, image classification has been a widely explored topic in mathematics, and many algorithms have proven to be effective classifiers. Howev…
Experimental Design for Non-Parametric Correction of Misspecified Dynamical Models
Gal Shulkind, Lior Horesh, Haim Avron
We consider a class of misspecified dynamical models where the governing term is only approximately known. Under the assumption that observations of the system's evolution are acce…
General Optimization Framework for Robust and Regularized 3D Full Waveform Inversion
Stephen Becker, Lior Horesh, Aleksandr Aravkin +1
Scarcity of hydrocarbon resources and high exploration risks motivate the development of high fidelity algorithms and computationally viable approaches to exploratory geophysics. W…