Siddhartha Mishra
Orcid: 0000-0002-2665-5385
According to our database1,
Siddhartha Mishra
authored at least 88 papers
between 2005 and 2024.
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Bibliography
2024
wPINNs: Weak Physics Informed Neural Networks for Approximating Entropy Solutions of Hyperbolic Conservation Laws.
SIAM J. Numer. Anal., 2024
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models.
CoRR, 2024
Numerical analysis of physics-informed neural networks and related models in physics-informed machine learning.
CoRR, 2024
2023
J. Comput. Phys., April, 2023
An operator preconditioning perspective on training in physics-informed machine learning.
CoRR, 2023
Multilevel domain decomposition-based architectures for physics-informed neural networks.
CoRR, 2023
CoRR, 2023
A Monte-Carlo ab-initio algorithm for the multiscale simulation of compressible multiphase flows.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Finite basis physics-informed neural networks as a Schwarz domain decomposition method.
CoRR, 2022
Error analysis for deep neural network approximations of parametric hyperbolic conservation laws.
CoRR, 2022
CoRR, 2022
Error estimates for physics informed neural networks approximating the Navier-Stokes equations.
CoRR, 2022
Error analysis for physics-informed neural networks (PINNs) approximating Kolmogorov PDEs.
Adv. Comput. Math., 2022
Generic bounds on the approximation error for physics-informed (and) operator learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
SIAM J. Sci. Comput., 2021
Enhancing Accuracy of Deep Learning Algorithms by Training with Low-Discrepancy Sequences.
SIAM J. Numer. Anal., 2021
J. Mach. Learn. Res., 2021
A novel fourth-order WENO interpolation technique. A possible new tool designed for radiative transfer.
CoRR, 2021
CoRR, 2021
On the well-posedness of Bayesian inversion for PDEs with ill-posed forward problems.
CoRR, 2021
CoRR, 2021
CoRR, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies.
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
On the Convergence of the Spectral Viscosity Method for the Two-Dimensional Incompressible Euler Equations with Rough Initial Data.
Found. Comput. Math., 2020
Iterative Surrogate Model Optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks.
CoRR, 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs II: A class of inverse problems.
CoRR, 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs.
CoRR, 2020
2019
CoRR, 2019
Statistical solutions of hyperbolic systems of conservation laws: numerical approximation.
CoRR, 2019
Automatic Identification of Mixed Retinal Cells in Time-Lapse Fluorescent Microscopy Images using High-Dimensional DBSCAN.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
2018
SIAM J. Numer. Anal., 2018
A machine learning framework for data driven acceleration of computations of differential equations.
CoRR, 2018
2017
Construction of Approximate Entropy Measure-Valued Solutions for Hyperbolic Systems of Conservation Laws.
Found. Comput. Math., 2017
2016
SIAM J. Math. Anal., 2016
Entropy stability and well-balancedness of space-time DG for the shallow water equations with bottom topography.
Networks Heterog. Media, 2016
SIAM/ASA J. Uncertain. Quantification, 2016
Multi-level Monte Carlo finite volume methods for uncertainty quantification of acoustic wave propagation in random heterogeneous layered medium.
J. Comput. Phys., 2016
2015
2014
Entropy stable shock capturing space-time discontinuous Galerkin schemes for systems of conservation laws.
Numerische Mathematik, 2014
Acta Numer., 2014
2013
Multi-level Monte Carlo Finite Volume Methods for Uncertainty Quantification in Nonlinear Systems of Balance Laws.
Proceedings of the Uncertainty Quantification in Computational Fluid Dynamics, 2013
Entropy Conservative and Entropy Stable Schemes for Nonconservative Hyperbolic Systems.
SIAM J. Numer. Anal., 2013
Convergence of vanishing capillarity approximations for scalar conservation laws with discontinuous fluxes.
Networks Heterog. Media, 2013
2012
Multilevel Monte Carlo Finite Volume Methods for Shallow Water Equations with Uncertain Topography in Multi-dimensions.
SIAM J. Sci. Comput., 2012
Arbitrarily High-order Accurate Entropy Stable Essentially Nonoscillatory Schemes for Systems of Conservation Laws.
SIAM J. Numer. Anal., 2012
Sparse tensor multi-level Monte Carlo finite volume methods for hyperbolic conservation laws with random initial data.
Math. Comput., 2012
J. Sci. Comput., 2012
Multi-level Monte Carlo finite volume methods for nonlinear systems of conservation laws in multi-dimensions.
J. Comput. Phys., 2012
2011
SIAM J. Sci. Comput., 2011
Constraint Preserving Schemes Using Potential-Based Fluxes. II. Genuinely Multidimensional Systems of Conservation Laws.
SIAM J. Numer. Anal., 2011
Well-balanced and energy stable schemes for the shallow water equations with discontinuous topography.
J. Comput. Phys., 2011
J. Comput. Appl. Math., 2011
Proceedings of the Parallel Processing and Applied Mathematics, 2011
2010
Convergence of an Engquist-Osher scheme for a multi-dimensional triangular system of conservation laws.
Math. Comput., 2010
2009
Numerische Mathematik, 2009
Well-balanced schemes for conservation laws with source terms based on a local discontinuous flux formulation.
Math. Comput., 2009
J. Sci. Comput., 2009
2007
Existence and stability of entropy solutions for a conservation law with discontinuous non-convex fluxes.
Networks Heterog. Media, 2007
Convergence of Godunov type methods for a conservation law with a spatially varying discontinuous flux function.
Math. Comput., 2007
2005
Convergence of Upwind Finite Difference Schemes for a Scalar Conservation Law with Indefinite Discontinuities in the Flux Function.
SIAM J. Numer. Anal., 2005