activity
20182026
most citedChallenges in Training PINNs: A Loss Landscape Perspective

40 citations · 41 across the 7 of their papers we have counts for

collaborators

8 papers

cs.LG2026

GPU-Enabled Large-Scale Optimization Using Randomized Linear Algebra

Pratik Rathore, Zachary Frangella, Parth Nobel +2

This paper introduces rlaopt, a PyTorch-based package for large-scale optimization and scientific computing using randomized numerical linear algebra (RandNLA). Despite substantial…

cs.LG2026

SubsurfaceGen: Procedural Generation of Field-Scale Earth Models and Seismic Data

Joseph Stitt, Pratik Rathore, Madeleine Udell +1

Full waveform inversion (FWI) is the gold standard for subsurface imaging, with applications from carbon sequestration to energy and mineral exploration to earthquake hazard assess…

cs.LG2025

Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project

Pratik Rathore, Zachary Frangella, Sachin Garg +3

Gaussian processes (GPs) play an essential role in biostatistics, scientific machine learning, and Bayesian optimization for their ability to provide probabilistic predictions and…

cs.LG2024★ 1 cited

Have ASkotch: A Neat Solution for Large-scale Kernel Ridge Regression

Pratik Rathore, Zachary Frangella, Jiaming Yang +2

Kernel ridge regression (KRR) is a fundamental computational tool, appearing in problems that range from computational chemistry to health analytics, with a particular interest due…

cs.LG2024★ 40 cited

Challenges in Training PINNs: A Loss Landscape Perspective

Pratik Rathore, Weimu Lei, Zachary Frangella +2

This paper explores challenges in training Physics-Informed Neural Networks (PINNs), emphasizing the role of the loss landscape in the training process. We examine difficulties in…

math.OC2023

PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates

Zachary Frangella, Pratik Rathore, Shipu Zhao +1

This paper introduces PROMISE (econditioned Stochastic ptimization ethods by ncorporating calable Curvature $\textbf{E}…

math.OC2022

SketchySGD: Reliable Stochastic Optimization via Randomized Curvature Estimates

Zachary Frangella, Pratik Rathore, Shipu Zhao +1

SketchySGD improves upon existing stochastic gradient methods in machine learning by using randomized low-rank approximations to the subsampled Hessian and by introducing an automa…

math.NT2018

There are no Cube-free Descartes Numbers with Exactly Seven Distinct Prime Factors

Pratik Rathore

We call an odd positive integer a if there exist positive integers such that and \begin{equation} σ(k)(m+1) = 2km \end{equation} Curr…