Arvind Mohan

According to our database, Arvind Mohan authored at least 6 papers between 2018 and 2024.

Collaborative distances:

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

2024

What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learning.

Arvind Mohan, Ashesh Chattopadhyay, Jonah Miller

CoRR, 2024

Machine learned reconstruction of tsunami dynamics from sparse observations.

Edward McDugald, Arvind Mohan, Darren Engwirda, Agnese Marcato, Javier E. Santos

CoRR, 2024

2023

Development of the Senseiver for efficient field reconstruction from sparse observations.

Javier E. Santos, Zachary R. Fox, Arvind Mohan, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers

Nat. Mac. Intell., October, 2023

Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra.

Ajeeta Khatiwada, Marc Louis Klasky, Marcie Lombardi, Jason Matheny, Arvind Mohan

CoRR, 2023

2019

The ISTI Rapid Response on Exploring Cloud Computing 2018.

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 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

CoRR, 2019

2018

From Deep to Physics-Informed Learning of Turbulence: Diagnostics.

Ryan King, Oliver Hennigh, Arvind Mohan, Michael Chertkov

CoRR, 2018