Daniel M. Tartakovsky

89 papers A* 1Journal 83Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs. SIAM J. Sci. Comput. Adrienne M. Propp, Jonas A. Actor, Elise Walker, Houman Owhadi, Nathaniel Trask, Daniel M. Tartakovsky
2026	J	`jnl`	Regional surrogates for predictive control of digital twins. J. Comput. Phys. Yuchen Zhang, Daniel M. Tartakovsky
2025	J	`jnl`	CODE: A global approach to ODE dynamics learning. CoRR Nils Wildt, Daniel M. Tartakovsky, Sergey Oladyshkin, Wolfgang Nowak
2025	J	`jnl`	Discovery of Linear Representations for Nonautonomous Translation-Invariant Problems. SIAM J. Sci. Comput. Hongli Zhao, Daniel M. Tartakovsky
2025	J	`jnl`	Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs. CoRR Adrienne M. Propp, Jonas A. Actor, Elise Walker, Houman Owhadi, Nathaniel Trask, Daniel M. Tartakovsky
2025	J	`jnl`	Domain-Decomposed Graph Neural Network Surrogate Modeling for Ice Sheets. CoRR Adrienne M. Propp, Mauro Perego, Eric C. Cyr, Anthony Gruber, Amanda A. Howard, Alexander Heinlein, Panos Stinis, Daniel M. Tartakovsky
2025	J	`jnl`	Generalizable models of magnetic hysteresis via physics-aware recurrent neural networks. Comput. Phys. Commun. Abhishek Chandra, Taniya Kapoor, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M. Tartakovsky, Elena A. Lomonova
2025	J	`jnl`	Information Worth and Assimilation of Binary Data. SIAM J. Sci. Comput. Apoorv Srivastava, Wei Kang, Daniel M. Tartakovsky
2025	J	`jnl`	Neural Differential Equation-Based Two-Stage Approach for Generalization of Beam Dynamics. IEEE Trans. Ind. Informatics Taniya Kapoor, Hongrui Wang, Anastasios Stamou, Kareem El Sayed, Alfredo Núñez, Daniel M. Tartakovsky, Rolf P. B. J. Dollevoet
2024	J	`jnl`	Baseflow identification via explainable AI with Kolmogorov-Arnold networks. CoRR Chuyang Liu, Tirthankar Roy, Daniel M. Tartakovsky, Dipankar Dwivedi
2024	J	`jnl`	Data-driven models of nonautonomous systems. J. Comput. Phys. Hannah Lu, Daniel M. Tartakovsky
2024	J	`jnl`	Efficient quadratures for high-dimensional Bayesian data assimilation. J. Comput. Phys. Ming Cheng, Peng Wang, Daniel M. Tartakovsky
2024	J	`jnl`	High-Precision Geosteering via Reinforcement Learning and Particle Filters. CoRR Ressi Bonti Muhammad, Apoorv Srivastava, Sergey Alyaev, Reidar Brumer Bratvold, Daniel M. Tartakovsky
2024	J	`jnl`	High-order Lagrangian algorithms for Liouville models of particle-laden flows. J. Comput. Phys. Daniel Domínguez-Vázquez, Sergio A. Castiblanco-Ballesteros, Gustaaf B. Jacobs, Daniel M. Tartakovsky
2024	A*	`conf`	Neural Oscillators for Generalization of Physics-Informed Machine Learning. AAAI Taniya Kapoor, Abhishek Chandra, Daniel M. Tartakovsky, Hongrui Wang, Alfredo Núñez, Rolf P. B. J. Dollevoet
2024	J	`jnl`	Surrogate models of heat transfer in fractured rock and their use in parameter estimation. Comput. Geosci. Guofeng Song, Delphine Roubinet, Xiaoguang Wang, Gensheng Li, Xianzhi Song, Daniel M. Tartakovsky
2024	J	`jnl`	Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling. CoRR Adrienne M. Propp, Daniel M. Tartakovsky
2023	J	`jnl`	DRIPS: A framework for dimension reduction and interpolation in parameter space. J. Comput. Phys. Hannah Lu, Daniel M. Tartakovsky
2023	J	`jnl`	Discovering Sparse Hysteresis Models: A Data-driven Study for Piezoelectric Materials and Perspectives on Magnetic Hysteresis. CoRR Abhishek Chandra, Bram Daniels, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky
2023	J	`jnl`	Feature-informed data assimilation. J. Comput. Phys. Apoorv Srivastava, Wei Kang, Daniel M. Tartakovsky
2023	J	`jnl`	Learning Nonautonomous Systems via Dynamic Mode Decomposition. CoRR Hannah Lu, Daniel M. Tartakovsky
2023	J	`jnl`	Neural oscillators for generalization of physics-informed machine learning. CoRR Taniya Kapoor, Abhishek Chandra, Daniel M. Tartakovsky, Hongrui Wang, Alfredo Núñez, Rolf P. B. J. Dollevoet
2023	J	`jnl`	Neural oscillators for magnetic hysteresis modeling. CoRR Abhishek Chandra, Taniya Kapoor, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M. Tartakovsky, Elena A. Lomonova
2023	J	`jnl`	Parsimonious models of in-host viral dynamics and immune response. Appl. Math. Lett. Hannah Lu, Francesco Giannino, Daniel M. Tartakovsky
2023	J	`jnl`	Physics-Aware Reduced-Order Modeling of Nonautonomous Advection-Dominated Problems. CoRR Hongli Zhao, Daniel M. Tartakovsky
2022	J	`jnl`	Feature-Informed Data Assimilation - Definitions and Illustrative Examples. CoRR Wei Kang, Daniel M. Tartakovsky, Apoorv Srivastava
2022	J	`jnl`	Information geometry of physics-informed statistical manifolds and its use in data assimilation. J. Comput. Phys. Francesca Boso, Daniel M. Tartakovsky
2022	J	`jnl`	Machine Learning in Heterogeneous Porous Materials. CoRR Marta D'Elia, Hang Deng, Cedric G. Fraces, Krishna C. Garikipati, Lori Graham-Brady, Amanda A. Howard, George Em Karniadakis, Vahid Keshavarzzadeh, Robert M. Kirby, J. Nathan Kutz, Chunhui Li, Xing Liu, Hannah Lu, Pania Newell, Daniel O'Malley, Masa Prodanovic, Gowri Srinivasan, Alexandre M. Tartakovsky, Daniel M. Tartakovsky, Hamdi A. Tchelepi, Bozo Vazic, Hari S. Viswanathan, Hongkyu Yoon, Piotr Zarzycki
2022	J	`jnl`	Model Reduction via Dynamic Mode Decomposition. CoRR Hannah Lu, Daniel M. Tartakovsky
2022	—	`conf`	Physics-informed neural networks for modelling anisotropic and bi-anisotropic electromagnetic constitutive laws through indirect data. SSCI Abhishek Chandra, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky
2022	J	`jnl`	Polynomial Chaos Expansions for Stiff Random ODEs. SIAM J. Sci. Comput. Wenjie Shi, Daniel M. Tartakovsky
2021	J	`jnl`	Data-driven discovery of coarse-grained equations. J. Comput. Phys. Joseph Bakarji, Daniel M. Tartakovsky
2021	J	`jnl`	Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties. CoRR Zitong Zhou, Nicholas Zabaras, Daniel M. Tartakovsky
2021	J	`jnl`	Dynamics of Data-driven Ambiguity Sets for Hyperbolic Conservation Laws with Uncertain Inputs. SIAM J. Sci. Comput. Francesca Boso, Dimitris Boskos, Jorge Cortés, Sonia Martínez, Daniel M. Tartakovsky
2021	J	`jnl`	Extended dynamic mode decomposition for inhomogeneous problems. J. Comput. Phys. Hannah Lu, Daniel M. Tartakovsky
2021	J	`jnl`	GINNs: Graph-Informed Neural Networks for multiscale physics. J. Comput. Phys. Eric Joseph Hall, Søren Taverniers, Markos A. Katsoulakis, Daniel M. Tartakovsky
2021	—	`conf`	Graph-Informed Neural Networks. AAAI Spring Symposium: MLPS Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
2021	J	`jnl`	Mutual information for explainable deep learning of multiscale systems. J. Comput. Phys. Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
2021	J	`jnl`	Transfer Learning on Multi-Fidelity Data. CoRR Dong H. Song, Daniel M. Tartakovsky
2020	J	`jnl`	Autonomous learning of nonlocal stochastic neuron dynamics. CoRR Tyler E. Maltba, Hongli Zhao, Daniel M. Tartakovsky
2020	J	`jnl`	Data-Driven Discovery of Coarse-Grained Equations. CoRR Joseph Bakarji, Daniel M. Tartakovsky
2020	J	`jnl`	Data-Informed Method of Distributions for Hyperbolic Conservation Laws. SIAM J. Sci. Comput. Francesca Boso, Daniel M. Tartakovsky
2020	J	`jnl`	Dynamic Mode Decomposition for Construction of Reduced-Order Models of Hyperbolic Problems with Shocks. CoRR Hannah Lu, Daniel M. Tartakovsky
2020	J	`jnl`	Estimation of distributions via multilevel Monte Carlo with stratified sampling. J. Comput. Phys. Søren Taverniers, Daniel M. Tartakovsky
2020	J	`jnl`	Extended Dynamic Mode Decomposition for Inhomogeneous Problems. CoRR Hannah Lu, Daniel M. Tartakovsky
2020	J	`jnl`	GINNs: Graph-Informed Neural Networks for Multiscale Physics. CoRR Eric Joseph Hall, Søren Taverniers, Markos A. Katsoulakis, Daniel M. Tartakovsky
2020	J	`jnl`	Lagrangian dynamic mode decomposition for construction of reduced-order models of advection-dominated phenomena. J. Comput. Phys. Hannah Lu, Daniel M. Tartakovsky
2020	J	`jnl`	Markov Chain Monte Carlo with Neural Network Surrogates: Application to Contaminant Source Identification. CoRR Zitong Zhou, Daniel M. Tartakovsky
2020	J	`jnl`	Modified immersed boundary method for flows over randomly rough surfaces. J. Comput. Phys. Chunsong Kwon, Daniel M. Tartakovsky
2020	J	`jnl`	Mutual Information for Explainable Deep Learning of Multiscale Systems. CoRR Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
2020	J	`jnl`	Prediction Accuracy of Dynamic Mode Decomposition. SIAM J. Sci. Comput. Hannah Lu, Daniel M. Tartakovsky
2020	J	`jnl`	Resource-Constrained Model Selection for Uncertainty Propagation and Data Assimilation. SIAM/ASA J. Uncertain. Quantification Lun Yang, Peng Wang, Daniel M. Tartakovsky
2020	J	`jnl`	Tensor methods for the Boltzmann-BGK equation. J. Comput. Phys. Arnout M. P. Boelens, Daniele Venturi, Daniel M. Tartakovsky
2019	J	`jnl`	Causality and Bayesian Network PDEs for multiscale representations of porous media. J. Comput. Phys. Kimoon Um, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
2019	J	`jnl`	Estimation of distributions via multilevel Monte Carlo with stratified sampling. CoRR Søren Taverniers, Daniel M. Tartakovsky
2019	J	`jnl`	Lagrangian Dynamic Mode Decomposition for Construction of Reduced-Order Models of Advection-Dominated Phenomena. CoRR Hannah Lu, Daniel M. Tartakovsky
2018	J	`jnl`	Nonlocal PDF methods for Langevin equations with colored noise. J. Comput. Phys. Tyler Maltba, Pierre-Alain Gremaud, Daniel M. Tartakovsky
2018	J	`jnl`	Parallel tensor methods for high-dimensional linear PDEs. J. Comput. Phys. Arnout M. P. Boelens, Daniele Venturi, Daniel M. Tartakovsky
2017	J	`jnl`	A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems. J. Comput. Phys. Søren Taverniers, Daniel M. Tartakovsky
2017	J	`jnl`	Doubly Penalized LASSO for Reconstruction of Biological Networks. Proc. IEEE Behrang Asadi, Mano Ram Maurya, Daniel M. Tartakovsky, Shankar Subramaniam
2017	J	`jnl`	Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor. J. Comput. Phys. Søren Taverniers, Daniel M. Tartakovsky
2017	J	`jnl`	On the use of reverse Brownian motion to accelerate hybrid simulations. J. Comput. Phys. Joseph Bakarji, Daniel M. Tartakovsky
2017	—	`conf`	Role of glycocalyx in attenuation of shear stress on endothelial cells: From in vivo experiments to microfluidic circuits. ECCTD Ilenia Battiato, Daniel M. Tartakovsky, Pedro J. Cabrales, Marcos Intaglietta
2016	J	`jnl`	Conservative tightly-coupled simulations of stochastic multiscale systems. J. Comput. Phys. Søren Taverniers, Alexander Y. Pigarov, Daniel M. Tartakovsky
2016	J	`jnl`	Stochastic Collocation Methods for Nonlinear Parabolic Equations with Random Coefficients. SIAM/ASA J. Uncertain. Quantification David A. Barajas-Solano, Daniel M. Tartakovsky
2015	J	`jnl`	Impact of Data Assimilation on Cost-Accuracy Tradeoff in Multifidelity Models. SIAM/ASA J. Uncertain. Quantification Michael Sinsbeck, Daniel M. Tartakovsky
2015	J	`jnl`	Impact of stochastic fluctuations in the cell free layer on nitric oxide bioavailability. Frontiers Comput. Neurosci. Sang-Woo Park, Marcos Intaglietta, Daniel M. Tartakovsky
2014	J	`jnl`	Information theoretic approach to complex biological network reconstruction: application to cytokine release in RAW 264.7 macrophages. BMC Syst. Biol. Farzaneh Farhangmehr, Mano Ram Maurya, Daniel M. Tartakovsky, Shankar Subramaniam
2014	J	`jnl`	Noise propagation in hybrid models of nonlinear systems: The Ginzburg-Landau equation. J. Comput. Phys. Søren Taverniers, Francis J. Alexander, Daniel M. Tartakovsky
2013	J	`jnl`	A New Physiological Boundary Condition for Hemodynamics. SIAM J. Appl. Math. Will Cousins, Pierre-Alain Gremaud, Daniel M. Tartakovsky
2013	—	`conf`	An information-theoretic algorithm to data-driven genetic pathway interaction network reconstruction of dynamic systems. BIBM Farzaneh Farhangmehr, Daniel M. Tartakovsky, Parastou Sadatmousavi, Mano Ram Maurya, Shankar Subramaniam
2013	J	`jnl`	CDF Solutions of Buckley-Leverett Equation with Uncertain Parameters. Multiscale Model. Simul. Peng Wang, Daniel M. Tartakovsky, K. D. Jarman Jr., Alexandre M. Tartakovsky
2013	J	`jnl`	Exact PDF equations and closure approximations for advective-reactive transport. J. Comput. Phys. Daniele Venturi, Daniel M. Tartakovsky, Alexandre M. Tartakovsky, George E. Karniadakis
2013	J	`jnl`	Particle-tracking simulations of anomalous transport in hierarchically fractured rocks. Comput. Geosci. Delphine Roubinet, Jean-Raynald de Dreuzy, Daniel M. Tartakovsky
2012	—	`conf`	Doubly Penalized LASSO for Reconstruction of Biological Networks. HISB Behrang Asadi, Daniel M. Tartakovsky, Mano Ram Maurya, Shankar Subramaniam
2012	J	`jnl`	Uncertainty quantification in kinematic-wave models. J. Comput. Phys. Peng Wang, Daniel M. Tartakovsky
2010	J	`jnl`	Random walk particle tracking simulations of non-Fickian transport in heterogeneous media. J. Comput. Phys. Gowri Srinivasan, Daniel M. Tartakovsky, Marco Dentz, Hari S. Viswanathan, Brian Berkowitz, B. A. Robinson
2010	J	`jnl`	Uncertainty quantification via random domain decomposition and probabilistic collocation on sparse grids. J. Comput. Phys. Guang Lin, Alexandre M. Tartakovsky, Daniel M. Tartakovsky
2008	J	`jnl`	Hybrid Simulations of Reaction-Diffusion Systems in Porous Media. SIAM J. Sci. Comput. Alexandre M. Tartakovsky, Daniel M. Tartakovsky, Timothy D. Scheibe, Paul Meakin
2007	J	`jnl`	Guest Editors' Introduction: Stochastic Modeling of Complex Systems. Comput. Sci. Eng. Daniel M. Tartakovsky, Dongbin Xiu
2006	J	`jnl`	Multivariate sensitivity analysis of saturated flow through simulated highly heterogeneous groundwater aquifers. J. Comput. Phys. C. L. Winter, Alberto Guadagnini, Douglas W. Nychka, Daniel M. Tartakovsky
2006	J	`jnl`	Numerical Methods for Differential Equations in Random Domains. SIAM J. Sci. Comput. Dongbin Xiu, Daniel M. Tartakovsky
2006	J	`jnl`	Stochastic analysis of transport in tubes with rough walls. J. Comput. Phys. Daniel M. Tartakovsky, Dongbin Xiu
2006	J	`jnl`	Subsurface characterization with support vector machines. IEEE Trans. Geosci. Remote. Sens. Brendt Wohlberg, Daniel M. Tartakovsky, Alberto Guadagnini
2005	J	`jnl`	Guest Editors' Introduction: Multiphysics Modeling. Comput. Sci. Eng. Daniel M. Tartakovsky, Francis J. Alexander
2005	J	`jnl`	Noise in algorithm refinement methods. Comput. Sci. Eng. Francis J. Alexander, Daniel M. Tartakovsky, Alejandro L. Garcia
2004	J	`jnl`	A Two-Scale Nonperturbative Approach to Uncertainty Analysis of Diffusion in Random Composites. Multiscale Model. Simul. Dongbin Xiu, Daniel M. Tartakovsky
2004	J	`jnl`	Effective Properties of Random Composites. SIAM J. Sci. Comput. Daniel M. Tartakovsky, Alberto Guadagnini
2001	J	`jnl`	Dynamics of Free Surfaces in Random Porous Media. SIAM J. Appl. Math. Daniel M. Tartakovsky, C. L. Winter