Suryanarayana Maddu

According to our database, Suryanarayana Maddu authored at least 13 papers between 2019 and 2024.

Collaborative distances:

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

2024

Learning fast, accurate, and stable closures of a kinetic theory of an active fluid.

Suryanarayana Maddu, Scott Weady, Michael J. Shelley

J. Comput. Phys., 2024

Inferring biological processes with intrinsic noise from cross-sectional data.

Suryanarayana Maddu, Victor Chardès, Michael J. Shelley

CoRR, 2024

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning.

Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina J. Agocs, Miguel Beneitez, Marsha Berger, Blakesley Burkhart, Stuart B. Dalziel, Drummond B. Fielding, Daniel Fortunato, Jared A. Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich R. Kerswell, Suryanarayana Maddu, Jonah Miller, Payel Mukhopadhyay, Stefan S. Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, François Rozet, Liam Holden Parker, Miles D. Cranmer, Shirley Ho

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems.

Sarah Perez, Suryanarayana Maddu, Ivo F. Sbalzarini, Philippe Poncet

J. Comput. Phys., October, 2023

Stochastic force inference via density estimation.

Victor Chardès, Suryanarayana Maddu, Michael J. Shelley

CoRR, 2023

Learning locally dominant force balances in active particle systems.

Dominik Sturm, Suryanarayana Maddu, Ivo F. Sbalzarini

CoRR, 2023

2022

Parallel Discrete Convolutions on Adaptive Particle Representations of Images.

Joel Jonsson, Bevan L. Cheeseman, Suryanarayana Maddu, Krzysztof Gonciarz, Ivo F. Sbalzarini

IEEE Trans. Image Process., 2022

Inverse Dirichlet weighting enables reliable training of physics informed neural networks.

Suryanarayana Maddu, Dominik Sturm, Christian L. Müller, Ivo F. Sbalzarini

Mach. Learn. Sci. Technol., 2022

Learning deterministic hydrodynamic equations from stochastic active particle dynamics.

Suryanarayana Maddu, Quentin Vagne, Ivo F. Sbalzarini

CoRR, 2022

2021

Data-driven modeling and simulation of spatiotemporal processes with a view toward applications in biology

Suryanarayana Maddu

PhD thesis, 2021

STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations.

Suryanarayana Maddu, Dominik Sturm, Bevan L. Cheeseman, Christian L. Müller, Ivo F. Sbalzarini

CoRR, 2021

2020

Learning physically consistent mathematical models from data using group sparsity.

Suryanarayana Maddu, Bevan L. Cheeseman, Christian L. Müller, Ivo F. Sbalzarini

CoRR, 2020

2019

Stability selection enables robust learning of partial differential equations from limited noisy data.

Suryanarayana Maddu, Bevan L. Cheeseman, Ivo F. Sbalzarini, Christian L. Müller

CoRR, 2019