← Search

Pratik Rathore

2 accepted papers

2025

Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project

NeurIPS 2025poster

Gaussian processes (GPs) play an essential role in biostatistics, scientific machine learning, and Bayesian optimization for their ability to provide probabilistic predictions and model uncertainty. However, GP inference struggles to scale to large datasets (which are common in modern applications),…

Cited by 0SourcecodeScholar
2024

Challenges in Training PINNs: A Loss Landscape Perspective

ICML 2024oral

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 minimizing the PINN loss function, particularly due to ill-conditioning caused by differential operators in the residual…