Suryanarayana Maddu

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All published works

Action	Title	Year	Authors
+	Learning locally dominant force balances in active particle systems	2024	Dominik Sturm Suryanarayana Maddu Ivo F. Sbalzarini
+ PDF Chat	The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning	2024	Ruben Ohana Michael T. McCabe Lucas Meyer Rudy Morel Fruzsina J. Agocs Miguel Beneitez Marsha Berger Blakesley Burkhart Stuart B. Dalziel Drummond B. Fielding
+ PDF Chat	Inferring biological processes with intrinsic noise from cross-sectional data	2024	Suryanarayana Maddu Victor Chardès Michael Shelley
+ PDF Chat	Learning fast, accurate, and stable closures of a kinetic theory of an active fluid	2024	Suryanarayana Maddu Scott Weady Michael Shelley
+	Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems	2023	Sarah Perez Suryanarayana Maddu Ivo F. Sbalzarini Philippe Poncet
+	Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems	2023	Sarah Perez Suryanarayana Maddu Ivo F. Sbalzarini Philippe Poncet
+	Learning locally dominant force balances in active particle systems	2023	Dominik Sturm Suryanarayana Maddu Ivo F. Sbalzarini
+	Learning fast, accurate, and stable closures of a kinetic theory of an active fluid	2023	Suryanarayana Maddu Scott Weady Michael Shelley
+ PDF Chat	Learning Fast, Accurate, and Stable Closures of a Kinetic Theory of an Active Fluid	2023	Suryanarayana Maddu Scott Weady Michael Shelley
+	Stochastic force inference via density estimation	2023	Victor Chardès Suryanarayana Maddu Michael Shelley
+	Stability selection enables robust learning of differential equations from limited noisy data	2022	Suryanarayana Maddu Bevan L. Cheeseman Ivo F. Sbalzarini Christian L. Müller
+	Learning deterministic hydrodynamic equations from stochastic active particle dynamics	2022	Suryanarayana Maddu Quentin Vagne Ivo F. Sbalzarini
+ PDF Chat	Parallel Discrete Convolutions on Adaptive Particle Representations of Images	2022	Joel Jonsson Bevan L. Cheeseman Suryanarayana Maddu Krzysztof Gonciarz Ivo F. Sbalzarini
+ PDF Chat	Parallel Discrete Convolutions on Adaptive Particle Representations of Images	2021	Joel Jonsson Bevan L. Cheeseman Suryanarayana Maddu Krzysztof Gonciarz Ivo F. Sbalzarini
+	Inverse Dirichlet weighting enables reliable training of physics informed neural networks	2021	Suryanarayana Maddu Dominik Sturm Christian L. Müller Ivo F. Sbalzarini
+	Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks	2021	Suryanarayana Maddu Dominik Sturm Christian L. Müller Ivo F. Sbalzarini
+ PDF Chat	Learning physically consistent differential equation models from data using group sparsity	2021	Suryanarayana Maddu Bevan L. Cheeseman Christian L. Müller Ivo F. Sbalzarini
+	STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations	2021	Suryanarayana Maddu Dominik Sturm Bevan L. Cheeseman Christian L. Müller Ivo F. Sbalzarini
+	Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks	2021	Suryanarayana Maddu Dominik Sturm Christian L. Müller Ivo F. Sbalzarini
+ PDF Chat	Lattice Boltzmann method for thin-liquid-film hydrodynamics	2019	Stefan Zitz Andrea Scagliarini Suryanarayana Maddu Anton A. Darhuber Jens Harting
+	Stability selection enables robust learning of partial differential equations from limited noisy data	2019	Suryanarayana Maddu Bevan L. Cheeseman Ivo F. Sbalzarini Christian L. Müller

Common Coauthors

Coauthor	Papers Together
Ivo F. Sbalzarini	14
Bevan L. Cheeseman	6
Christian L. Müller	6
Michael Shelley	5
Dominik Sturm	3
Dominik Sturm	3
Scott Weady	3
Krzysztof Gonciarz	2
Sarah Perez	2
Victor Chardès	2
Philippe Poncet	2
Ruben Ohana	1
Stuart B. Dalziel	1
Yan-Fei Jiang	1
Michael T. McCabe	1
Liam Parker	1
Blakesley Burkhart	1
Shirley Ho	1
Jens Harting	1
Joel Jonsson	1
Christian L. Müller	1
Jonah Miller	1
Quentin Vagne	1
Rudy Morel	1
Jianfu Shen	1
Fruzsina J. Agocs	1
Miles Cranmer	1
Stefan Zitz	1
Miguel Beneitez	1
Payel Mukhopadhyay	1
Keiya Hirashima	1
François Rozet	1
Jared A. Goldberg	1
S. W. Nixon	1
Andrea Scagliarini	1
Anton A. Darhuber	1
Joel Jonsson	1
Romain Watteaux	1
Marsha Berger	1
Bruno Régaldo-Saint Blancard	1
Rich R. Kerswell	1
Lucas Meyer	1
Daniel Fortunato	1
Drummond B. Fielding	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Discovering governing equations from data by sparse identification of nonlinear dynamical systems	2016	Steven L. Brunton Joshua L. Proctor J. Nathan Kutz	6
+ PDF Chat	Data-driven discovery of partial differential equations	2017	Samuel Rudy Steven L. Brunton Joshua L. Proctor J. Nathan Kutz	5
+ PDF Chat	Estimating the Dimension of a Model	1978	Gideon Schwarz	3
+ PDF Chat	Fluid Dynamics of Bacterial Turbulence	2013	Jörn Dunkel Sebastian Heidenreich Knut Drescher H. H. Wensink Markus Bär Raymond E. Goldstein	3
+	B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data	2020	Liu Yang Xuhui Meng George Em Karniadakis	3
+ PDF Chat	Learning partial differential equations via data discovery and sparse optimization	2017	Hayden Schaeffer	3
+	Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data	2019	Luning Sun Han Gao Shaowu Pan Jianxun Wang	3
+	Stability selection enables robust learning of differential equations from limited noisy data	2022	Suryanarayana Maddu Bevan L. Cheeseman Ivo F. Sbalzarini Christian L. Müller	3
+ PDF Chat	Deep learning of dynamics and signal-noise decomposition with time-stepping constraints	2019	Samuel Rudy J. Nathan Kutz Steven L. Brunton	3
+ PDF Chat	Stability Selection	2010	Nicolai Meinshausen Peter Bühlmann	3
+	OpenFPM: A scalable open framework for particle and particle-mesh codes on parallel computers	2019	Pietro Incardona Antonio Leo Yaroslav Zaluzhnyi Rajesh Ramaswamy Ivo F. Sbalzarini	3
+ PDF Chat	Subspace Pursuit for Compressive Sensing Signal Reconstruction	2009	Wei Dai Olgica Milenković	3
+ PDF Chat	Learning physically consistent differential equation models from data using group sparsity	2021	Suryanarayana Maddu Bevan L. Cheeseman Christian L. Müller Ivo F. Sbalzarini	3
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	3
+ PDF Chat	DeepMoD: Deep learning for model discovery in noisy data	2020	Gert-Jan Both Subham Choudhury Pierre Sens Rémy Kusters	3
+	Convex Optimization	2004	Stephen Boyd Lieven Vandenberghe	3
+	Iterative hard thresholding for compressed sensing	2009	Thomas Blumensath Mike E. Davies	3
+	CoSaMP: Iterative signal recovery from incomplete and inaccurate samples	2008	Deanna Needell Joel A. Tropp	3
+ PDF Chat	PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network	2019	Zichao Long Yiping Lu Bin Dong	3
+ PDF Chat	Machine learning of linear differential equations using Gaussian processes	2017	Maziar Raissi Paris Perdikaris George Em Karniadakis	3
+ PDF Chat	Deep learning of turbulent scalar mixing	2019	Maziar Raissi Hessam Babaee Peyman Givi	2
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	2
+ PDF Chat	A variational level set methodology without reinitialization for the prediction of equilibrium interfaces over arbitrary solid surfaces	2019	Karim Alamé Sreevatsa Anantharamu Krishnan Mahesh	2
+ PDF Chat	On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators	1992	Jonathan Eckstein Dimitri P. Bertsekas	2
+	Exponential Time Differencing for Stiff Systems	2002	Stephen M. Cox P. C. Matthews	2
+ PDF Chat	Non-Convex Global Minimization and False Discovery Rate Control for the TREX	2017	Jacob Bien Irina Gaynanova Johannes Lederer Christian L. Müller	2
+ PDF Chat	Multi-task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics	2018	Roberto Cipolla Yarin Gal Alex Kendall	2
+ PDF Chat	Flocks, herds, and schools: A quantitative theory of flocking	1998	John Toner Yuhai Tu	2
+ PDF Chat	Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics	2016	Niall M. Mangan Steven L. Brunton Joshua L. Proctor J. Nathan Kutz	2
+ PDF Chat	fPINNs: Fractional Physics-Informed Neural Networks	2019	Guofei Pang Lu Lu George Em Karniadakis	2
+	Biology by numbers: mathematical modelling in developmental biology	2007	Claire J. Tomlin Jeffrey D. Axelrod	2
+	Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)	2009	Martin J. Wainwright	2
+ PDF Chat	Proximal Splitting Methods in Signal Processing	2011	Patrick L. Combettes Jean‐Christophe Pesquet	2
+	Stability selection enables robust learning of partial differential equations from limited noisy data	2019	Suryanarayana Maddu Bevan L. Cheeseman Ivo F. Sbalzarini Christian L. Müller	2
+	Understanding and mitigating gradient pathologies in physics-informed neural networks	2020	Sifan Wang Yujun Teng Paris Perdikaris	2
+	Solving high-dimensional partial differential equations using deep learning	2018	Jiequn Han Arnulf Jentzen E Weinan	2
+	Regularization Paths for Generalized Linear Models via Coordinate Descent.	2010	Jerome H. Friedman Trevor Hastie Rob Tibshirani	2
+	DGM: A deep learning algorithm for solving partial differential equations	2018	Justin Sirignano Konstantinos Spiliopoulos	2
+	Data smoothing and numerical differentiation by a regularization method	2009	Jonathan J. Stickel	2
+	Sobolev Training for Neural Networks	2017	Wojciech Marian Czarnecki Simon Osindero Max Jaderberg Grzegorz Świrszcz Razvan Pascanu	2
+	Meso-scale turbulence in living fluids	2012	H. H. Wensink Jörn Dunkel Sebastian Heidenreich Knut Drescher Raymond E. Goldstein Hartmut Löwen Julia M. Yeomans	2
+	Hidden physics models: Machine learning of nonlinear partial differential equations	2017	Maziar Raissi George Em Karniadakis	2
+	A Note on Parseval's Theorem for Fourier Transforms	1931	G. H. Hardy E. C. Titchmarsh	2
+	Identification of continuous, spatiotemporal systems	1998	Henning U. Voss M. J. Bünner Mathieu Abel	2
+	Estimating Optimal Transformations for Multiple Regression and Correlation	1985	Leo Breiman Jerome H. Friedman	2
+	Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties	2001	Jianqing Fan Runze Li	2
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	2
+	Finite Difference Methods in Financial Engineering: A Partial Differential Equation Approach	2006	Daniel J. Duffy	2
+ PDF Chat	Parameter Estimation of Partial Differential Equation Models	2013	Xiaolei Xun Jiguo Cao Bani K. Mallick Arnab Maity Raymond J. Carroll	2
+	Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models.	2010	Han Liu Kathryn Roeder Larry Wasserman	2