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Willie Padilla

3 accepted papers

2022

Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions

ICLR 2022poster

Numerous physical systems are described by ordinary or partial differential equations whose solutions are given by holomorphic or meromorphic functions in the complex domain. In many cases, only the magnitude of these functions are observed on various points on the purely imaginary $j\omega$-axis si…

Cited by 0SourcePDFScholar
2021

Benchmarking Data-driven Surrogate Simulators for Artificial Electromagnetic Materials

NeurIPS 2021poster

Artificial electromagnetic materials (AEMs), including metamaterials, derive their electromagnetic properties from geometry rather than chemistry. With the appropriate geometric design, AEMs have achieved exotic properties not realizable with conventional materials (e.g., cloaking or negative refrac…

Cited by 17SourceScholar
2020

Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method

NeurIPS 2020poster

We consider the task of solving generic inverse problems, where one wishes to determine the hidden parameters of a natural system that will give rise to a particular set of measurements. Recently many new approaches based upon deep learning have arisen, generating promising results. We conceptualize…