Nonlinear integro-differential operator regression with neural networks. - Ravi G. Patel; Olivier Desjardins (CoRR, 2018)

GMLS-Nets: A framework for learning from unstructured data. - Nathaniel Trask; Ravi G. Patel; Ben J. Gross; Paul J. Atzberger (CoRR, 2019)

Three-dimensional conditional hyperbolic quadrature method of moments. - Ravi G. Patel; Olivier Desjardins; Rodney O. Fox (J. Comput. Phys. X, 2019)

GMLS-Nets: A Machine Learning Framework for Unstructured Data. - Nathaniel Trask; Ravi G. Patel; Paul J. Atzberger; Ben J. Gross (AAAI Spring Symposium: MLPS, 2020)

Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint. - Eric C. Cyr; Mamikon A. Gulian; Ravi G. Patel; Mauro Perego; Nathaniel A. Trask (MSML, 2020)

A physics-informed operator regression framework for extracting data-driven continuum models. - Ravi G. Patel; Nathaniel A. Trask; Mitchell A. Wood; Eric C. Cyr (CoRR, 2020)

Partition of Unity Networks: Deep HP-Approximation. - Kookjin Lee; Nathaniel Trask; Ravi G. Patel; Mamikon A. Gulian; Eric C. Cyr (AAAI Spring Symposium: MLPS, 2021)

A Block Coordinate Descent Optimizer for Classification Problems Exploiting Convexity. - Ravi G. Patel; Nathaniel Trask; Mamikon A. Gulian; Eric C. Cyr (AAAI Spring Symposium: MLPS, 2021)

Reduced Basis Approximations of Parameterized Dynamical Partial Differential Equations via Neural Networks. - Peter Sentz; Kristian Beckwith; Eric C. Cyr; Luke N. Olson; Ravi G. Patel (CoRR, 2021)

Error-in-variables modelling for operator learning. - Ravi G. Patel; Indu Manickam; Myoungkyu Lee; Mamikon A. Gulian (MSML, 2022)

Thermodynamically consistent physics-informed neural networks for hyperbolic systems. - Ravi G. Patel; Indu Manickam; Nathaniel A. Trask; Mitchell A. Wood; Myoungkyu Lee; Ignacio Tomas; Eric C. Cyr (J. Comput. Phys., 2022)

Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes. - Jeremiah Hauth; Cosmin Safta; Xun Huan; Ravi G. Patel; Reese E. Jones (CoRR, 2024)

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response. - Ravi G. Patel; Cosmin Safta; Reese E. Jones (CoRR, 2024)

Analog Bayesian neural networks are insensitive to the shape of the weight distribution. - Ravi G. Patel; T. Patrick Xiao; Sapan Agarwal; Christopher H. Bennett (CoRR, 2025)

Mixture of neural operator experts for learning boundary conditions and model selection. - Dwyer Deighan; Jonas A. Actor; Ravi G. Patel (CoRR, 2025)

Uncertainty quantification of neural network models of evolving processes via Langevin sampling. - Cosmin Safta; Reese E. Jones; Ravi G. Patel; Raelynn Wonnacott; Dan S. Bolintineanu; Craig M. Hamel; Sharlotte L. B. Kramer (CoRR, 2025)