6 citations · 24 across the 10 of their papers we have counts for
4 papers · 1 filter
Structure-preserving learning for multi-symplectic PDEs
Süleyman Yıldız, Pawan Goyal, Peter Benner
This paper presents an energy-preserving machine learning method for inferring reduced-order models (ROMs) by exploiting the multi-symplectic form of partial differential equations…
Neural ODEs with Irregular and Noisy Data
Pawan Goyal, Peter Benner
Measurement noise is an integral part while collecting data of a physical process. Thus, noise removal is necessary to draw conclusions from these data, and it often becomes essent…
Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint
Pawan Goyal, Peter Benner
Measurement noise is an integral part while collecting data of a physical process. Thus, noise removal is a necessary step to draw conclusions from these data, and it often becomes…
LQResNet: A Deep Neural Network Architecture for Learning Dynamic Processes
Pawan Goyal, Peter Benner
Mathematical modeling is an essential step, for example, to analyze the transient behavior of a dynamical process and to perform engineering studies such as optimization and contro…