Vivek Oommen

According to our database, Vivek Oommen authored at least 16 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Spectral bias in physics-informed and operator learning: Analysis and mitigation guidelines.

Siavash Khodakarami, Vivek Oommen, Nazanin Ahmadi Daryakenari, Maxim Beekenkamp, George Em Karniadakis

CoRR, February, 2026

Mitigating spectral bias in neural operators via high-frequency scaling for physical systems.

Siavash Khodakarami, Vivek Oommen, Aniruddha Bora, George Em Karniadakis

Neural Networks, 2026

2025

A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning.

Juan Diego Toscano, Daniel T. Chen, Vivek Oommen, Jérôme Darbon, George Em Karniadakis

CoRR, September, 2025

Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstruction.

Vivek Oommen, Siavash Khodakarami, Aniruddha Bora, Zhicheng Wang, George Em Karniadakis

CoRR, September, 2025

Equilibrium Conserving Neural Operators for Super-Resolution Learning.

Vivek Oommen, Andreas E. Robertson, Daniel Diaz, Coleman Alleman, Zhen Zhang, Anthony D. Rollett, George E. Karniadakis, Rémi Dingreville

CoRR, April, 2025

XAI4Extremes: An interpretable machine learning framework for understanding extreme-weather precursors under climate change.

Jiawen Wei, Aniruddha Bora, Vivek Oommen, Chenyu Dong, Juntao Yang, Jeff Adie, Chen Chen, Simon See, George E. Karniadakis, Gianmarco Mengaldo

CoRR, March, 2025

Importance of localized dilatation and distensibility in identifying determinants of thoracic aortic aneurysm with neural operators.

David S. Li, Somdatta Goswami, Qianying Cao, Vivek Oommen, Roland Assi, Jay D. Humphrey, George E. Karniadakis

PLoS Comput. Biol., 2025

2024

Deep neural operators as accurate surrogates for shape optimization.

Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Nicholas Plewacki, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis

Eng. Appl. Artif. Intell., 2024

From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning.

Juan Diego Toscano, Vivek Oommen, Alan John Varghese, Zongren Zou, Nazanin Ahmadi Daryakenari, Chenxi Wu, George Em Karniadakis

CoRR, 2024

Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling.

Vivek Oommen, Aniruddha Bora, Zhen Zhang, George Em Karniadakis

CoRR, 2024

RiemannONets: Interpretable Neural Operators for Riemann Problems.

Ahmad Peyvan, Vivek Oommen, Ameya D. Jagtap, George Em Karniadakis

CoRR, 2024

2023

Rethinking materials simulations: Blending direct numerical simulations with neural operators.

Vivek Oommen, Khemraj Shukla, Saaketh Desai, Rémi Dingreville, George Em Karniadakis

CoRR, 2023

GPT vs Human for Scientific Reviews: A Dual Source Review on Applications of ChatGPT in Science.

Chenxi Wu, Alan John Varghese, Vivek Oommen, George Em Karniadakis

CoRR, 2023

Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils.

Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis

CoRR, 2023

2022

Solving Inverse Heat Transfer Problems Without Surrogate Models: A Fast, Data-Sparse, Physics Informed Neural Network Approach.

Vivek Oommen, Balaji Srinivasan

J. Comput. Inf. Sci. Eng., 2022

Learning two-phase microstructure evolution using neural operators and autoencoder architectures.

Vivek Oommen, Khemraj Shukla, Somdatta Goswami, Rémi Dingreville, George Em Karniadakis

CoRR, 2022