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ORCIDDaniel M. Tartakovsky
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2020 – today
- 2024
[j52]Guofeng Song
, Delphine Roubinet, Xiaoguang Wang, Gensheng Li, Xianzhi Song, Daniel M. Tartakovsky:
Surrogate models of heat transfer in fractured rock and their use in parameter estimation. Comput. Geosci. 183: 105509 (2024)- [j51]Ming Cheng, Peng Wang, Daniel M. Tartakovsky:
Efficient quadratures for high-dimensional Bayesian data assimilation. J. Comput. Phys. 506: 112945 (2024) - [j50]Hannah Lu, Daniel M. Tartakovsky:
Data-driven models of nonautonomous systems. J. Comput. Phys. 507: 112976 (2024) - [j49]Daniel Domínguez-Vázquez, Sergio A. Castiblanco-Ballesteros, Gustaaf B. Jacobs, Daniel M. Tartakovsky:
High-order Lagrangian algorithms for Liouville models of particle-laden flows. J. Comput. Phys. 515: 113281 (2024) - [c6]Taniya Kapoor, Abhishek Chandra, Daniel M. Tartakovsky, Hongrui Wang, Alfredo Núñez, Rolf P. B. J. Dollevoet:
Neural Oscillators for Generalization of Physics-Informed Machine Learning. AAAI 2024: 13059-13067 - [i20]Ressi Bonti Muhammad, Apoorv Srivastava, Sergey Alyaev, Reidar Brumer Bratvold, Daniel M. Tartakovsky:
High-Precision Geosteering via Reinforcement Learning and Particle Filters. CoRR abs/2402.06377 (2024) - 2023
- [j48]Hannah Lu, Francesco Giannino, Daniel M. Tartakovsky:
Parsimonious models of in-host viral dynamics and immune response. Appl. Math. Lett. 145: 108781 (2023) - [j47]Hannah Lu, Daniel M. Tartakovsky:
DRIPS: A framework for dimension reduction and interpolation in parameter space. J. Comput. Phys. 493: 112455 (2023) - [j46]Apoorv Srivastava, Wei Kang, Daniel M. Tartakovsky:
Feature-informed data assimilation. J. Comput. Phys. 494: 112499 (2023) - [i19]Abhishek Chandra, Bram Daniels, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky:
Discovering Sparse Hysteresis Models: A Data-driven Study for Piezoelectric Materials and Perspectives on Magnetic Hysteresis. CoRR abs/2302.05313 (2023) - [i18]Hannah Lu, Daniel M. Tartakovsky:
Learning Nonautonomous Systems via Dynamic Mode Decomposition. CoRR abs/2306.15618 (2023) - [i17]Taniya Kapoor, Abhishek Chandra, Daniel M. Tartakovsky, Hongrui Wang, Alfredo Núñez, Rolf P. B. J. Dollevoet:
Neural oscillators for generalization of physics-informed machine learning. CoRR abs/2308.08989 (2023) - [i16]Abhishek Chandra, Taniya Kapoor, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M. Tartakovsky, Elena A. Lomonova:
Neural oscillators for magnetic hysteresis modeling. CoRR abs/2308.12002 (2023) - [i15]Hongli Zhao, Daniel M. Tartakovsky:
Physics-Aware Reduced-Order Modeling of Nonautonomous Advection-Dominated Problems. CoRR abs/2309.05117 (2023) - 2022
- [j45]Francesca Boso, Daniel M. Tartakovsky:
Information geometry of physics-informed statistical manifolds and its use in data assimilation. J. Comput. Phys. 467: 111438 (2022) - [j44]Wenjie Shi, Daniel M. Tartakovsky:
Polynomial Chaos Expansions for Stiff Random ODEs. SIAM J. Sci. Comput. 44(3): 1021- (2022) - [c5]Abhishek Chandra, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky:
Physics-informed neural networks for modelling anisotropic and bi-anisotropic electromagnetic constitutive laws through indirect data. SSCI 2022: 1451-1459 - [i14]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:
Machine Learning in Heterogeneous Porous Materials. CoRR abs/2202.04137 (2022) - [i13]Hannah Lu, Daniel M. Tartakovsky:
Model Reduction via Dynamic Mode Decomposition. CoRR abs/2204.09590 (2022) - [i12]Wei Kang, Daniel M. Tartakovsky, Apoorv Srivastava:
Feature-Informed Data Assimilation - Definitions and Illustrative Examples. CoRR abs/2211.00256 (2022) - 2021
- [j43]Eric Joseph Hall, Søren Taverniers, Markos A. Katsoulakis, Daniel M. Tartakovsky:
GINNs: Graph-Informed Neural Networks for multiscale physics. J. Comput. Phys. 433: 110192 (2021) - [j42]Joseph Bakarji, Daniel M. Tartakovsky:
Data-driven discovery of coarse-grained equations. J. Comput. Phys. 434: 110219 (2021) - [j41]Hannah Lu, Daniel M. Tartakovsky:
Extended dynamic mode decomposition for inhomogeneous problems. J. Comput. Phys. 444: 110550 (2021) - [j40]Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky:
Mutual information for explainable deep learning of multiscale systems. J. Comput. Phys. 444: 110551 (2021) - [j39]Francesca Boso, Dimitris Boskos, Jorge Cortés, Sonia Martínez, Daniel M. Tartakovsky:
Dynamics of Data-driven Ambiguity Sets for Hyperbolic Conservation Laws with Uncertain Inputs. SIAM J. Sci. Comput. 43(3): A2102-A2129 (2021) - [c4]Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky:
Graph-Informed Neural Networks. AAAI Spring Symposium: MLPS 2021 - [i11]Dong H. Song, Daniel M. Tartakovsky:
Transfer Learning on Multi-Fidelity Data. CoRR abs/2105.00856 (2021) - [i10]Zitong Zhou, Nicholas Zabaras, Daniel M. Tartakovsky:
Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties. CoRR abs/2110.12367 (2021) - 2020
- [j38]Chunsong Kwon, Daniel M. Tartakovsky:
Modified immersed boundary method for flows over randomly rough surfaces. J. Comput. Phys. 406: 109195 (2020) - [j37]Hannah Lu, Daniel M. Tartakovsky:
Lagrangian dynamic mode decomposition for construction of reduced-order models of advection-dominated phenomena. J. Comput. Phys. 407: 109229 (2020) - [j36]Søren Taverniers, Daniel M. Tartakovsky:
Estimation of distributions via multilevel Monte Carlo with stratified sampling. J. Comput. Phys. 419: 109572 (2020) - [j35]Arnout M. P. Boelens, Daniele Venturi, Daniel M. Tartakovsky:
Tensor methods for the Boltzmann-BGK equation. J. Comput. Phys. 421: 109744 (2020) - [j34]Lun Yang, Peng Wang, Daniel M. Tartakovsky:
Resource-Constrained Model Selection for Uncertainty Propagation and Data Assimilation. SIAM/ASA J. Uncertain. Quantification 8(3): 1118-1138 (2020) - [j33]Francesca Boso, Daniel M. Tartakovsky:
Data-Informed Method of Distributions for Hyperbolic Conservation Laws. SIAM J. Sci. Comput. 42(1): A559-A583 (2020) - [j32]Hannah Lu, Daniel M. Tartakovsky:
Prediction Accuracy of Dynamic Mode Decomposition. SIAM J. Sci. Comput. 42(3): A1639-A1662 (2020) - [i9]Joseph Bakarji, Daniel M. Tartakovsky:
Data-Driven Discovery of Coarse-Grained Equations. CoRR abs/2002.00790 (2020) - [i8]Zitong Zhou, Daniel M. Tartakovsky:
Markov Chain Monte Carlo with Neural Network Surrogates: Application to Contaminant Source Identification. CoRR abs/2003.02322 (2020) - [i7]Hannah Lu, Daniel M. Tartakovsky:
Dynamic Mode Decomposition for Construction of Reduced-Order Models of Hyperbolic Problems with Shocks. CoRR abs/2003.12165 (2020) - [i6]Hannah Lu, Daniel M. Tartakovsky:
Extended Dynamic Mode Decomposition for Inhomogeneous Problems. CoRR abs/2004.06205 (2020) - [i5]Eric Joseph Hall, Søren Taverniers, Markos A. Katsoulakis, Daniel M. Tartakovsky:
GINNs: Graph-Informed Neural Networks for Multiscale Physics. CoRR abs/2006.14807 (2020) - [i4]Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky:
Mutual Information for Explainable Deep Learning of Multiscale Systems. CoRR abs/2009.04570 (2020) - [i3]Tyler E. Maltba, Hongli Zhao, Daniel M. Tartakovsky:
Autonomous learning of nonlocal stochastic neuron dynamics. CoRR abs/2011.10955 (2020)
2010 – 2019
- 2019
- [j31]Kimoon Um, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky:
Causality and Bayesian Network PDEs for multiscale representations of porous media. J. Comput. Phys. 394: 658-678 (2019) - [i2]Søren Taverniers, Daniel M. Tartakovsky:
Estimation of distributions via multilevel Monte Carlo with stratified sampling. CoRR abs/1906.00126 (2019) - [i1]Hannah Lu, Daniel M. Tartakovsky:
Lagrangian Dynamic Mode Decomposition for Construction of Reduced-Order Models of Advection-Dominated Phenomena. CoRR abs/1908.03688 (2019) - 2018
- [j30]Tyler Maltba, Pierre-Alain Gremaud, Daniel M. Tartakovsky:
Nonlocal PDF methods for Langevin equations with colored noise. J. Comput. Phys. 367: 87-101 (2018) - [j29]Arnout M. P. Boelens, Daniele Venturi, Daniel M. Tartakovsky:
Parallel tensor methods for high-dimensional linear PDEs. J. Comput. Phys. 375: 519-539 (2018) - 2017
- [j28]Søren Taverniers, Daniel M. Tartakovsky:
A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems. J. Comput. Phys. 330: 884-901 (2017) - [j27]Joseph Bakarji, Daniel M. Tartakovsky:
On the use of reverse Brownian motion to accelerate hybrid simulations. J. Comput. Phys. 334: 68-80 (2017) - [j26]Søren Taverniers, Daniel M. Tartakovsky:
Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor. J. Comput. Phys. 348: 139-150 (2017) - [j25]Behrang Asadi, Mano Ram Maurya, Daniel M. Tartakovsky, Shankar Subramaniam:
Doubly Penalized LASSO for Reconstruction of Biological Networks. Proc. IEEE 105(2): 319-329 (2017) - [c3]Ilenia Battiato, Daniel M. Tartakovsky, Pedro J. Cabrales, Marcos Intaglietta:
Role of glycocalyx in attenuation of shear stress on endothelial cells: From in vivo experiments to microfluidic circuits. ECCTD 2017: 1-4 - 2016
- [j24]Søren Taverniers, Alexander Y. Pigarov, Daniel M. Tartakovsky:
Conservative tightly-coupled simulations of stochastic multiscale systems. J. Comput. Phys. 313: 400-414 (2016) - [j23]David A. Barajas-Solano, Daniel M. Tartakovsky:
Stochastic Collocation Methods for Nonlinear Parabolic Equations with Random Coefficients. SIAM/ASA J. Uncertain. Quantification 4(1): 475-494 (2016) - 2015
- [j22]Sang-Woo Park, Marcos Intaglietta, Daniel M. Tartakovsky:
Impact of stochastic fluctuations in the cell free layer on nitric oxide bioavailability. Frontiers Comput. Neurosci. 9: 131 (2015) - [j21]Michael Sinsbeck, Daniel M. Tartakovsky:
Impact of Data Assimilation on Cost-Accuracy Tradeoff in Multifidelity Models. SIAM/ASA J. Uncertain. Quantification 3(1): 954-968 (2015) - 2014
- [j20]Farzaneh Farhangmehr, Mano Ram Maurya, Daniel M. Tartakovsky, Shankar Subramaniam:
Information theoretic approach to complex biological network reconstruction: application to cytokine release in RAW 264.7 macrophages. BMC Syst. Biol. 8: 77 (2014) - [j19]Søren Taverniers, Francis J. Alexander, Daniel M. Tartakovsky:
Noise propagation in hybrid models of nonlinear systems: The Ginzburg-Landau equation. J. Comput. Phys. 262: 313-324 (2014) - 2013
- [j18]Delphine Roubinet, Jean-Raynald de Dreuzy, Daniel M. Tartakovsky:
Particle-tracking simulations of anomalous transport in hierarchically fractured rocks. Comput. Geosci. 50: 52-58 (2013) - [j17]Daniele Venturi, Daniel M. Tartakovsky, Alexandre M. Tartakovsky, George E. Karniadakis:
Exact PDF equations and closure approximations for advective-reactive transport. J. Comput. Phys. 243: 323-343 (2013) - [j16]Peng Wang, Daniel M. Tartakovsky, K. D. Jarman Jr., Alexandre M. Tartakovsky:
CDF Solutions of Buckley-Leverett Equation with Uncertain Parameters. Multiscale Model. Simul. 11(1): 118-133 (2013) - [j15]Will Cousins, Pierre-Alain Gremaud, Daniel M. Tartakovsky:
A New Physiological Boundary Condition for Hemodynamics. SIAM J. Appl. Math. 73(3): 1203-1223 (2013) - [c2]Farzaneh Farhangmehr, Daniel M. Tartakovsky, Parastou Sadatmousavi, Mano Ram Maurya, Shankar Subramaniam:
An information-theoretic algorithm to data-driven genetic pathway interaction network reconstruction of dynamic systems. BIBM 2013: 214-217 - 2012
- [j14]Peng Wang, Daniel M. Tartakovsky:
Uncertainty quantification in kinematic-wave models. J. Comput. Phys. 231(23): 7868-7880 (2012) - [c1]Behrang Asadi, Daniel M. Tartakovsky, Mano Ram Maurya, Shankar Subramaniam:
Doubly Penalized LASSO for Reconstruction of Biological Networks. HISB 2012: 129 - 2010
- [j13]Gowri Srinivasan, Daniel M. Tartakovsky, Marco Dentz, Hari S. Viswanathan, Brian Berkowitz, B. A. Robinson:
Random walk particle tracking simulations of non-Fickian transport in heterogeneous media. J. Comput. Phys. 229(11): 4304-4314 (2010) - [j12]G. Lin, Alexandre M. Tartakovsky, Daniel M. Tartakovsky:
Uncertainty quantification via random domain decomposition and probabilistic collocation on sparse grids. J. Comput. Phys. 229(19): 6995-7012 (2010)
2000 – 2009
- 2008
- [j11]Alexandre M. Tartakovsky, Daniel M. Tartakovsky, Timothy D. Scheibe, Paul Meakin:
Hybrid Simulations of Reaction-Diffusion Systems in Porous Media. SIAM J. Sci. Comput. 30(6): 2799-2816 (2008) - 2007
- [j10]Daniel M. Tartakovsky, Dongbin Xiu:
Guest Editors' Introduction: Stochastic Modeling of Complex Systems. Comput. Sci. Eng. 9(2): 8-9 (2007) - 2006
- [j9]C. L. Winter, Alberto Guadagnini, Douglas W. Nychka, Daniel M. Tartakovsky:
Multivariate sensitivity analysis of saturated flow through simulated highly heterogeneous groundwater aquifers. J. Comput. Phys. 217(1): 166-175 (2006) - [j8]Daniel M. Tartakovsky, Dongbin Xiu:
Stochastic analysis of transport in tubes with rough walls. J. Comput. Phys. 217(1): 248-259 (2006) - [j7]Dongbin Xiu, Daniel M. Tartakovsky:
Numerical Methods for Differential Equations in Random Domains. SIAM J. Sci. Comput. 28(3): 1167-1185 (2006) - [j6]Brendt Wohlberg, Daniel M. Tartakovsky, Alberto Guadagnini:
Subsurface characterization with support vector machines. IEEE Trans. Geosci. Remote. Sens. 44(1): 47-57 (2006) - 2005
- [j5]Daniel M. Tartakovsky, Francis J. Alexander:
Guest Editors' Introduction: Multiphysics Modeling. Comput. Sci. Eng. 7(3): 14-15 (2005) - [j4]Francis J. Alexander, Daniel M. Tartakovsky, Alejandro L. Garcia:
Noise in algorithm refinement methods. Comput. Sci. Eng. 7(3): 32-38 (2005) - 2004
- [j3]Dongbin Xiu, Daniel M. Tartakovsky:
A Two-Scale Nonperturbative Approach to Uncertainty Analysis of Diffusion in Random Composites. Multiscale Model. Simul. 2(4): 662-674 (2004) - [j2]Daniel M. Tartakovsky, Alberto Guadagnini:
Effective Properties of Random Composites. SIAM J. Sci. Comput. 26(2): 625-635 (2004) - 2001
- [j1]Daniel M. Tartakovsky, C. L. Winter:
Dynamics of Free Surfaces in Random Porous Media. SIAM J. Appl. Math. 61(6): 1857-1876 (2001)
Coauthor Index
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last updated on 2024-10-07 21:25 CEST by the dblp team
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