Suryanarayana Maddu

17 papers A* 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Inferring stochastic dynamics with growth from cross-sectional data. CoRR Stephen Zhang, Suryanarayana Maddu, Xiaojie Qiu, Victor Chardès
2024	J	`jnl`	Inferring biological processes with intrinsic noise from cross-sectional data. CoRR Suryanarayana Maddu, Victor Chardès, Michael J. Shelley
2024	J	`jnl`	Learning fast, accurate, and stable closures of a kinetic theory of an active fluid. J. Comput. Phys. Suryanarayana Maddu, Scott Weady, Michael J. Shelley
2024	A*	`conf`	The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning. NeurIPS Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina Julia 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
2024	J	`jnl`	The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning. CoRR Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina Julia 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
2023	J	`jnl`	Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems. J. Comput. Phys. Sarah Perez, Suryanarayana Maddu, Ivo F. Sbalzarini, Philippe Poncet
2023	J	`jnl`	Learning locally dominant force balances in active particle systems. CoRR Dominik Sturm, Suryanarayana Maddu, Ivo F. Sbalzarini
2023	J	`jnl`	Stochastic force inference via density estimation. CoRR Victor Chardès, Suryanarayana Maddu, Michael J. Shelley
2022	J	`jnl`	Inverse Dirichlet weighting enables reliable training of physics informed neural networks. Mach. Learn. Sci. Technol. Suryanarayana Maddu, Dominik Sturm, Christian L. Müller, Ivo F. Sbalzarini
2022	J	`jnl`	Learning deterministic hydrodynamic equations from stochastic active particle dynamics. CoRR Suryanarayana Maddu, Quentin Vagne, Ivo F. Sbalzarini
2022	J	`jnl`	Parallel Discrete Convolutions on Adaptive Particle Representations of Images. IEEE Trans. Image Process. Joel Jonsson, Bevan L. Cheeseman, Suryanarayana Maddu, Krzysztof Gonciarz, Ivo F. Sbalzarini
2021	—	`—`	Data-driven modeling and simulation of spatiotemporal processes with a view toward applications in biology Suryanarayana Maddu
2021	J	`jnl`	Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks. CoRR Suryanarayana Maddu, Dominik Sturm, Christian L. Müller, Ivo F. Sbalzarini
2021	J	`jnl`	Parallel Discrete Convolutions on Adaptive Particle Representations of Images. CoRR Joel Jonsson, Bevan L. Cheeseman, Suryanarayana Maddu, Krzysztof Gonciarz, Ivo F. Sbalzarini
2021	J	`jnl`	STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations. CoRR Suryanarayana Maddu, Dominik Sturm, Bevan L. Cheeseman, Christian L. Müller, Ivo F. Sbalzarini
2020	J	`jnl`	Learning physically consistent mathematical models from data using group sparsity. CoRR Suryanarayana Maddu, Bevan L. Cheeseman, Christian L. Müller, Ivo F. Sbalzarini
2019	J	`jnl`	Stability selection enables robust learning of partial differential equations from limited noisy data. CoRR Suryanarayana Maddu, Bevan L. Cheeseman, Ivo F. Sbalzarini, Christian L. Müller