Arvind T. Mohan

13 papers A 1Journal 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Binned spectral power loss for improved prediction of chaotic systems.
J. Comput. Phys.
Dibyajyoti Chakraborty, Arvind T. Mohan, Romit Maulik
2025 J jnl
Binned Spectral Power Loss for Improved Prediction of Chaotic Systems.
CoRR
Dibyajyoti Chakraborty, Arvind T. Mohan, Romit Maulik
2025 J jnl
Generalization vs. Memorization in Autoregressive Deep Learning: Or, Examining Temporal Decay of Gradient Coherence.
CoRR
James Amarel, Nicolas Hengartner, Robyn Miller, Kamaljeet Singh, Siddharth Mansingh, Arvind T. Mohan, Benjamin Migliori, Emily Casleton, Alexei N. Skurikhin, Earl Lawrence, Gerd J. Kunde
2025 J jnl
Physics-constrained coupled neural differential equations for one dimensional blood flow modeling.
Comput. Biol. Medicine
Hunor Csala, Arvind T. Mohan, Daniel Livescu, Amirhossein Arzani
2025 J jnl
Reduced Order Modeling for Tsunami Forecasting with Bayesian Hierarchical Pooling.
CoRR
Shane X. Coffing, John Tipton, Arvind T. Mohan, Darren Engwirda
2025 J jnl
Towards Reasoning for PDE Foundation Models: A Reward-Model-Driven Inference-Time-Scaling Algorithm.
CoRR
Siddharth Mansingh, James Amarel, Ragib Arnab, Arvind T. Mohan, Kamaljeet Singh, Gerd J. Kunde, Nicolas Hengartner, Benjamin Migliori, Emily Casleton, Nathan DeBardeleben, Ayan Biswas, Diane Oyen, Earl Lawrence
2024 J jnl
Machine learned reconstruction of tsunami dynamics from sparse observations.
CoRR
Edward McDugald, Arvind T. Mohan, Darren Engwirda, Agnese Marcato, Javier E. Santos
2024 J jnl
Physics-constrained coupled neural differential equations for one dimensional blood flow modeling.
CoRR
Hunor Csala, Arvind T. Mohan, Daniel Livescu, Amirhossein Arzani
2023 J jnl
Development of the Senseiver for efficient field reconstruction from sparse observations.
Nat. Mac. Intell.
Javier E. Santos, Zachary R. Fox, Arvind T. Mohan, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers
2022 J jnl
Physics-Constrained Generative Adversarial Networks for 3D Turbulence.
CoRR
Dima Tretiak, Arvind T. Mohan, Daniel Livescu
2020 A conf
Foresight: analysis that matters for data reduction.
SC
Pascal Grosset, Christopher M. Biwer, Jesus Pulido, Arvind T. Mohan, Ayan Biswas, John Patchett, Terece L. Turton, David H. Rogers, Daniel Livescu, James P. Ahrens
2019 J jnl
The ISTI Rapid Response on Exploring Cloud Computing 2018.
CoRR
Carleton Coffrin, James Arnold, Stephan J. Eidenbenz, Derek Aberle, John Ambrosiano, Zachary K. Baker, Sara Brambilla, Michael J. Brown, K. Nolan Carter, Pinghan Chu, Patrick Conry, Keeley Costigan, Ariane Eberhardt, David M. Fobes, Adam Gausmann, Sean N. Harris, Donovan Heimer, Marlin Holmes, Bill Junor, Csaba Kiss, Steve Linger, Rodman R. Linn, Li-Ta Lo, Jonathan MacCarthy, Omar Marcillo, Clay McGinnis, Alexander McQuarters, Eric Michalak, Arvind T. Mohan, Matt Nelson, Diane Oyen, Nidhi Parikh, Donatella Pasqualini, Aaron S. Pope, Reid B. Porter, Chris Rawlings, Hannah Reinbolt, Reid D. Rivenburgh, Philip Romero, Kevin Schoonover, Alexei N. Skurikhin, Daniel R. Tauritz, Dima Tretiak, Zhehui Wang, James Wernicke, Brad Wolfe, Phillip Wolfram, Jonathan Woodring
2018 J jnl
From Deep to Physics-Informed Learning of Turbulence: Diagnostics.
CoRR
Ryan King, Oliver Hennigh, Arvind T. Mohan, Michael Chertkov