most citedTransfer learning for improved generalizability in causal physics-informed neural networks for beam simulations

2 citations · 2 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2023★ 2 cited

Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations

Taniya Kapoor, Hongrui Wang, Alfredo Nunez +1

This paper introduces a novel methodology for simulating the dynamics of beams on elastic foundations. Specifically, Euler-Bernoulli and Timoshenko beam models on the Winkler found…

cs.LG2023

Neural oscillators for generalization of physics-informed machine learning

Taniya Kapoor, Abhishek Chandra, Daniel M. Tartakovsky +3

A primary challenge of physics-informed machine learning (PIML) is its generalization beyond the training domain, especially when dealing with complex physical problems represented…