Vivek Oommen - RankMe

18 papers Journal 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Mitigating spectral bias in neural operators via high-frequency scaling for physical systems. Neural Networks Siavash Khodakarami, Vivek Oommen, Aniruddha Bora, George Em Karniadakis
2026	J	`jnl`	Spectral bias in physics-informed and operator learning: Analysis and mitigation guidelines. CoRR Siavash Khodakarami, Vivek Oommen, Nazanin Ahmadi Daryakenari, Maxim Beekenkamp, George Em Karniadakis
2025	J	`jnl`	A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning. CoRR Juan Diego Toscano, Daniel T. Chen, Vivek Oommen, Jérôme Darbon, George Em Karniadakis
2025	J	`jnl`	Equilibrium Conserving Neural Operators for Super-Resolution Learning. CoRR Vivek Oommen, Andreas E. Robertson, Daniel Diaz, Coleman Alleman, Zhen Zhang, Anthony D. Rollett, George E. Karniadakis, Rémi Dingreville
2025	J	`jnl`	Importance of localized dilatation and distensibility in identifying determinants of thoracic aortic aneurysm with neural operators. CoRR David S. Li, Somdatta Goswami, Qianying Cao, Vivek Oommen, Roland Assi, Jay D. Humphrey, George E. Karniadakis
2025	J	`jnl`	Importance of localized dilatation and distensibility in identifying determinants of thoracic aortic aneurysm with neural operators. PLoS Comput. Biol. David S. Li, Somdatta Goswami, Qianying Cao, Vivek Oommen, Roland Assi, Jay D. Humphrey, George E. Karniadakis
2025	J	`jnl`	Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstruction. CoRR Vivek Oommen, Siavash Khodakarami, Aniruddha Bora, Zhicheng Wang, George Em Karniadakis
2025	J	`jnl`	Mitigating Spectral Bias in Neural Operators via High-Frequency Scaling for Physical Systems. CoRR Siavash Khodakarami, Vivek Oommen, Aniruddha Bora, George Em Karniadakis
2025	J	`jnl`	XAI4Extremes: An interpretable machine learning framework for understanding extreme-weather precursors under climate change. CoRR Jiawen Wei, Aniruddha Bora, Vivek Oommen, Chenyu Dong, Juntao Yang, Jeff Adie, Chen Chen, Simon See, George E. Karniadakis, Gianmarco Mengaldo
2024	J	`jnl`	Deep neural operators as accurate surrogates for shape optimization. Eng. Appl. Artif. Intell. Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Nicholas Plewacki, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis
2024	J	`jnl`	From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning. CoRR Juan Diego Toscano, Vivek Oommen, Alan John Varghese, Zongren Zou, Nazanin Ahmadi Daryakenari, Chenxi Wu, George Em Karniadakis
2024	J	`jnl`	Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling. CoRR Vivek Oommen, Aniruddha Bora, Zhen Zhang, George Em Karniadakis
2024	J	`jnl`	RiemannONets: Interpretable Neural Operators for Riemann Problems. CoRR Ahmad Peyvan, Vivek Oommen, Ameya D. Jagtap, George Em Karniadakis
2023	J	`jnl`	Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils. CoRR Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis
2023	J	`jnl`	GPT vs Human for Scientific Reviews: A Dual Source Review on Applications of ChatGPT in Science. CoRR Chenxi Wu, Alan John Varghese, Vivek Oommen, George Em Karniadakis
2023	J	`jnl`	Rethinking materials simulations: Blending direct numerical simulations with neural operators. CoRR Vivek Oommen, Khemraj Shukla, Saaketh Desai, Rémi Dingreville, George Em Karniadakis
2022	J	`jnl`	Learning two-phase microstructure evolution using neural operators and autoencoder architectures. CoRR Vivek Oommen, Khemraj Shukla, Somdatta Goswami, Rémi Dingreville, George Em Karniadakis
2022	J	`jnl`	Solving Inverse Heat Transfer Problems Without Surrogate Models: A Fast, Data-Sparse, Physics Informed Neural Network Approach. J. Comput. Inf. Sci. Eng. Vivek Oommen, Balaji Srinivasan