Karthik Duraisamy
Orcid: 0000-0002-3519-8147
According to our database1,
Karthik Duraisamy
authored at least 37 papers
between 2003 and 2024.
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Bibliography
2024
Information theoretic clustering for coarse-grained modeling of non-equilibrium gas dynamics.
J. Comput. Phys., 2024
Spatially-Aware Diffusion Models with Cross-Attention for Global Field Reconstruction with Sparse Observations.
CoRR, 2024
Finite Sample Analysis and Bounds of Generalization Error of Gradient Descent in In-Context Linear Regression.
CoRR, 2024
Enhancing Dynamical System Modeling through Interpretable Machine Learning Augmentations: A Case Study in Cathodic Electrophoretic Deposition.
CoRR, 2024
2023
Predictive reduced order modeling of chaotic multi-scale problems using adaptively sampled projections.
J. Comput. Phys., October, 2023
SoftwareX, February, 2023
CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems.
CoRR, 2023
Data-driven Balanced Truncation for Predictive Model Order Reduction of Aeroacoustic Response.
CoRR, 2023
CoRR, 2023
Proceedings of the American Control Conference, 2023
2022
PERFORM: A Python package for developing reduced-order models for reacting fluid flows.
J. Open Source Softw., November, 2022
Model reduction for multi-scale transport problems using model-form preserving least-squares projections with variable transformation.
J. Comput. Phys., 2022
Entropy-stable schemes in the low-Mach-number regime: Flux-preconditioning, entropy breakdowns, and entropy transfers.
J. Comput. Phys., 2022
A Non-intrusive Approach for Physics-constrained Learning with Application to Fuel Cell Modeling.
CoRR, 2022
2021
Non-intrusive Balancing Transformation of Highly Stiff Systems with Lightly-damped Impulse Response.
CoRR, 2021
CoRR, 2021
Non-linear Independent Dual System (NIDS) for Discretization-independent Surrogate Modeling over Complex Geometries.
CoRR, 2021
Variational Encoders and Autoencoders : Information-theoretic Inference and Closed-form Solutions.
CoRR, 2021
Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the NASA Formal Methods - 13th International Symposium, 2021
2020
Physics-Informed Probabilistic Learning of Linear Embeddings of Nonlinear Dynamics with Guaranteed Stability.
SIAM J. Appl. Dyn. Syst., 2020
2019
Multi-level Convolutional Autoencoder Networks for Parametric Prediction of Spatio-temporal Dynamics.
CoRR, 2019
CoRR, 2019
2018
Complex., 2018
2017
A dynamic subgrid scale model for Large Eddy Simulations based on the Mori-Zwanzig formalism.
J. Comput. Phys., 2017
2016
A paradigm for data-driven predictive modeling using field inversion and machine learning.
J. Comput. Phys., 2016
Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils.
CoRR, 2016
Parameter estimation in the Burgers equation using retrospective-cost model refinement.
Proceedings of the 2016 American Control Conference, 2016
2015
CoRR, 2015
Retrospective cost adaptive thrust control of a 1D scramjet with Mach number disturbance.
Proceedings of the American Control Conference, 2015
2011
Proceedings of the Conference on High Performance Computing Networking, 2011
2007
Implicit Scheme for Hyperbolic Conservation Laws Using Nonoscillatory Reconstruction in Space and Time.
SIAM J. Sci. Comput., 2007
2003
J. Sci. Comput., 2003