Concepts and Application of Time-Limiters to High Resolution Schemes. - Karthikeyan Duraisamy; James D. Baeder; Jian-Guo Liu 006 (J. Sci. Comput., 2003)

Implicit Scheme for Hyperbolic Conservation Laws Using Nonoscillatory Reconstruction in Space and Time. - Karthikeyan Duraisamy; James D. Baeder (SIAM J. Sci. Comput., 2007)

Liszt: a domain specific language for building portable mesh-based PDE solvers. - Zach DeVito; Niels Joubert; Francisco Palacios; Stephen Oakley; Montserrat Medina; Mike Barrientos; Erich Elsen; Frank Ham; Alex Aiken; Karthik Duraisamy; Eric Darve; Juan J. Alonso; et al. (SC, 2011)

Retrospective cost adaptive thrust control of a 1D scramjet with Mach number disturbance. - Ankit Goel; Antai Xie; Karthik Duraisamy; Dennis S. Bernstein (ACC, 2015)

Efficient Multiscale Gaussian Process Regression using Hierarchical Clustering. - Ze Jia Zhang; Karthik Duraisamy; Nail A. Gumerov (CoRR, 2015)

Parameter estimation in the Burgers equation using retrospective-cost model refinement. - Ankit Goel; Karthik Duraisamy; Dennis S. Bernstein (ACC, 2016)

Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils. - Anand Pratap Singh; Shivaji Medida; Karthik Duraisamy (CoRR, 2016)

A paradigm for data-driven predictive modeling using field inversion and machine learning. - Eric J. Parish; Karthik Duraisamy (J. Comput. Phys., 2016)

A dynamic subgrid scale model for Large Eddy Simulations based on the Mori-Zwanzig formalism. - Eric J. Parish; Karthik Duraisamy (J. Comput. Phys., 2017)

Long-Time Predictive Modeling of Nonlinear Dynamical Systems Using Neural Networks. - Shaowu Pan; Karthik Duraisamy (Complex., 2018)

Data-Driven Discovery of Closure Models. - Shaowu Pan; Karthik Duraisamy (SIAM J. Appl. Dyn. Syst., 2018)

Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks. - Yaser Afshar; Saakaar Bhatnagar; Shaowu Pan; Karthik Duraisamy; Shailendra Kaushik (CoRR, 2019)

Multi-level Convolutional Autoencoder Networks for Parametric Prediction of Spatio-temporal Dynamics. - Jiayang Xu; Karthik Duraisamy (CoRR, 2019)

Entropy Conservative Schemes and the Receding Flow Problem. - Ayoub Gouasmi; Scott M. Murman; Karthik Duraisamy (J. Sci. Comput., 2019)

Physics-Informed Probabilistic Learning of Linear Embeddings of Nonlinear Dynamics with Guaranteed Stability. - Shaowu Pan; Karthik Duraisamy (SIAM J. Appl. Dyn. Syst., 2020)

A Formal Proof of the Lax Equivalence Theorem for Finite Difference Schemes. - Mohit Tekriwal; Karthik Duraisamy; Jean-Baptiste Jeannin (NFM, 2021)

Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems. - Jiayang Xu; Aniruddhe Pradhan; Karthik Duraisamy (NeurIPS, 2021)

Variational Encoders and Autoencoders : Information-theoretic Inference and Closed-form Solutions. - Karthik Duraisamy (CoRR, 2021)

Non-linear Independent Dual System (NIDS) for Discretization-independent Surrogate Modeling over Complex Geometries. - James Duvall; Karthik Duraisamy; Shaowu Pan (CoRR, 2021)

Disentangling Generative Factors of Physical Fields Using Variational Autoencoders. - Christian Jacobsen; Karthik Duraisamy (CoRR, 2021)

Non-intrusive Balancing Transformation of Highly Stiff Systems with Lightly-damped Impulse Response. - Elnaz Rezaian; Cheng Huang; Karthik Duraisamy (CoRR, 2021)

A Non-intrusive Approach for Physics-constrained Learning with Application to Fuel Cell Modeling. - Vishal Srivastava; Valentin Sulzer; Peyman Mohtat; Jason B. Siegel; Karthik Duraisamy (CoRR, 2022)

Entropy-stable schemes in the low-Mach-number regime: Flux-preconditioning, entropy breakdowns, and entropy transfers. - Ayoub Gouasmi; Scott M. Murman; Karthik Duraisamy (J. Comput. Phys., 2022)

Model reduction for multi-scale transport problems using model-form preserving least-squares projections with variable transformation. - Cheng Huang; Christopher R. Wentland; Karthik Duraisamy; Charles L. Merkle (J. Comput. Phys., 2022)

PERFORM: A Python package for developing reduced-order models for reacting fluid flows. - Christopher R. Wentland; Karthik Duraisamy (J. Open Source Softw., 2022)

Control-aware Learning of Koopman Embedding Models. - Daisuke Uchida; Karthik Duraisamy (ACC, 2023)

On the lifting and reconstruction of dynamical systems with multiple attractors. - Shaowu Pan; Karthik Duraisamy (CoRR, 2023)

Data-driven Balanced Truncation for Predictive Model Order Reduction of Aeroacoustic Response. - Elnaz Rezaian; Karthik Duraisamy (CoRR, 2023)

Easy attention: A simple self-attention mechanism for Transformers. - Marcial Sanchis-Agudo; Yuning Wang; Karthik Duraisamy; Ricardo Vinuesa (CoRR, 2023)

PLATFORM: Parallel Linear Algebra Tool FOr Reduced Modeling. - Nicholas Arnold-Medabalimi; Christopher R. Wentland; Cheng Huang; Karthik Duraisamy (SoftwareX, 2023)

Predictive reduced order modeling of chaotic multi-scale problems using adaptively sampled projections. - Cheng Huang; Karthik Duraisamy (J. Comput. Phys., 2023)

Enhancing Dynamical System Modeling through Interpretable Machine Learning Augmentations: A Case Study in Cathodic Electrophoretic Deposition. - Christian Jacobsen; Jiayuan Dong; Mehdi Khalloufi; Xun Huan; Karthik Duraisamy; Maryam Akram; Wanjiao Liu (CoRR, 2024)

Variational Bayesian Optimal Experimental Design with Normalizing Flows. - Jiayuan Dong; Christian Jacobsen; Mehdi Khalloufi; Maryam Akram; Wanjiao Liu; Karthik Duraisamy; Xun Huan (CoRR, 2024)

Finite Sample Analysis and Bounds of Generalization Error of Gradient Descent in In-Context Linear Regression. - Karthik Duraisamy (CoRR, 2024)

Spatially-Aware Diffusion Models with Cross-Attention for Global Field Reconstruction with Sparse Observations. - Yilin Zhuang; Sibo Cheng; Karthik Duraisamy (CoRR, 2024)

Information theoretic clustering for coarse-grained modeling of non-equilibrium gas dynamics. - Christian Jacobsen; Ivan Zanardi; Sahil Bhola; Karthik Duraisamy; Marco Panesi (J. Comput. Phys., 2024)

Data-driven Koopman Operator-based Prediction and Control Using Model Averaging. - Daisuke Uchida; Karthik Duraisamy (ACC, 2025)

Extracting Koopman Operators for Prediction and Control of Nonlinear Dynamics Using Two-Stage Learning and Oblique Projections. - Daisuke Uchida; Karthik Duraisamy (SIAM J. Appl. Dyn. Syst., 2025)

CoCoGen: Physically Consistent and Conditioned Score-Based Generative Models for Forward and Inverse Problems. - Christian Jacobsen; Yilin Zhuang; Karthik Duraisamy (SIAM J. Sci. Comput., 2025)

LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather Forecasting. - Yilin Zhuang; Karthik Duraisamy (CoRR, 2025)

A Digital Twin Framework for Generation-IV Reactors with Reinforcement Learning-Enabled Health-Aware Supervisory Control. - Jasmin Y. Lim; Dimitrios Pylorof; Humberto E. Garcia; Karthik Duraisamy (CoRR, 2025)

Active Inference AI Systems for Scientific Discovery. - Karthik Duraisamy (CoRR, 2025)