Beyond first-order methods for non-convex non-concave min-max optimization

1 code implementation • 17 Apr 2023 • Abhijeet Vyas, Brian Bullins

We propose a study of structured non-convex non-concave min-max problems which goes beyond standard first-order approaches.

Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning

no code implementations • 30 Jan 2023 • Hrishikesh Viswanath, Md Ashiqur Rahman, Abhijeet Vyas, Andrey Shor, Beatriz Medeiros, Stephanie Hernandez, Suhas Eswarappa Prameela, Aniket Bera

This article aims to provide a comprehensive insight into how data-driven approaches can complement conventional techniques to solve engineering and physics problems, while also noting some of the major pitfalls of machine learning-based approaches.

Operator learning Physics-informed machine learning

Competitive Gradient Optimization

1 code implementation • 27 May 2022 • Abhijeet Vyas, Kamyar Azizzadenesheli

We provide a rate of convergence to stationary points and further propose a generalized class of $\alpha$-coherent function for which we provide convergence analysis.