Owhadi, Houman

Combined from CaltechAUTHORS

• Hamzi, Boumediene and Hutter, Marcus, et el. (2024) Bridging Algorithmic Information Theory and Machine Learning: A new approach to kernel learning; Physica D: Nonlinear Phenomena; Vol. 464; 134153; 10.1016/j.physd.2024.134153
• Owhadi, H. (2023) Gaussian process hydrodynamics; Applied Mathematics and Mechanics; 10.1007/s10483-023-2990-9
• Hamzi, Boumediene and Owhadi, Houman, et el. (2023) A note on microlocal kernel design for some slow–fast stochastic differential equations with critical transitions and application to EEG signals; Physica A; Vol. 616; Art. No. 128583; 10.1016/j.physa.2023.128583
• Owhadi, Houman (2023) Do ideas have shape? Idea registration as the continuous limit of artificial neural networks; Physica D; Vol. 444; Art. No. 133592; 10.1016/j.physd.2022.133592
• Darcy, Matthieu and Hamzi, Boumediene, et el. (2023) One-shot learning of stochastic differential equations with data adapted kernels; Physica D; Vol. 444; Art. No. 133583; 10.1016/j.physd.2022.133583
• Lee, Jonghyeon and De Brouwer, Edward, et el. (2023) Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series; Physica D; Vol. 443; Art. No. 133546; 10.1016/j.physd.2022.133546
• Akian, J.-L. and Bonnet, L., et el. (2022) Learning "best" kernels from data in Gaussian process regression. With application to aerodynamics; Journal of Computational Physics; Vol. 470; Art. No. 111595; 10.1016/j.jcp.2022.111595
• Smirnov, Alexandre and Hamzi, Boumediene, et el. (2022) Mean-field limits of trained weights in deep learning: A dynamical systems perspective; Dolomites Research Notes on Approximation; Vol. 15; No. 3; 125-145; 10.14658/pupj-drna-2022-3-12
• Owhadi, Houman (2022) Computational graph completion; Research in the Mathematical Sciences; Vol. 9; No. 2; Art. No. 27; 10.1007/s40687-022-00320-8
• Hamzi, Boumediene and Maulik, Romit, et el. (2022) Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methods; 10.48550/arXiv.2103.10935
• Hamze Bajgiran, Hamed and Owhadi, Houman (2022) Aggregation of Pareto optimal models; 10.48550/arXiv.2112.04161
• Hamze Bajgiran, Hamed and Batlle Franch, Pau, et el. (2022) Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball; 10.48550/arXiv.2108.10517
• Lee, Jonghyeon and De Brouwer, Edward, et el. (2022) Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time Series; 10.48550/arXiv.2111.13037
• Hamze Bajgiran, Hamed and Owhadi, Houman (2022) Aggregation of Models, Choices, Beliefs, and Preferences; 10.48550/arXiv.2111.11630
• Chen, Yifan and Hosseini, Bamdad, et el. (2021) Solving and learning nonlinear PDEs with Gaussian processes; Journal of Computational Physics; Vol. 447; Art. No. 110668; 10.1016/j.jcp.2021.110668
• Yoo, Gene Ryan and Owhadi, Houman (2021) Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows; Physica D: Nonlinear Phenomena; Vol. 426; Art. No. 132952; 10.1016/j.physd.2021.132952
• Hamzi, B. and Maulik, R., et el. (2021) Simple, low-cost and accurate data-driven geophysical forecasting with learned kernels; Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences; Vol. 477; No. 2252; Art. No. 20210326; 10.1098/rspa.2021.0326
• Hamzi, Boumediene and Owhadi, Houman (2021) Learning dynamical systems from data: A simple cross-validation perspective, part I: Parametric kernel flows; Physica D; Vol. 421; Art. No. 132817; 10.1016/j.physd.2020.132817
• Chen, Yifang and Owhadi, Houman, et el. (2021) Consistency of empirical Bayes and kernel flow for hierarchical parameter estimation; Mathematics of Computation; Vol. 90; 2527-2578; 10.1090/mcom/3649
• Schäfer, Florian and Katzfuss, Matthias, et el. (2021) Sparse Cholesky Factorization by Kullback-Leibler Minimization; SIAM Journal on Scientific Computing; Vol. 43; No. 3; A2019-A2046; 10.1137/20M1336254
• Schäfer, Florian and Sullivan, T. J., et el. (2021) Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity; Multiscale Modeling and Simulation; Vol. 19; No. 2; 688-730; 10.1137/19M129526X
• Tavallali, Peyman and Hamze Bajgiran, Hamed, et el. (2021) Decision Theoretic Bootstrapping; 10.48550/arXiv.2103.09982
• Hamzi, Boumediene and Owhadi, Houman (2020) Learning dynamical systems from data: a simple cross-validation perspective; 10.48550/arXiv.2007.05074
• Owhadi, Houman (2020) Do ideas have shape? Plato's theory of forms as the continuous limit of artificial neural networks; 10.48550/arXiv.2008.03920
• Schäfer, Florian and Anandkumar, Anima, et el. (2020) Competitive Mirror Descent; 10.48550/arXiv.2006.10179
• Xie, Hehu and Zhang, Lei, et el. (2019) Fast eigenpairs computation with operator adapted wavelets and hierarchical subspace correction; SIAM Journal on Numerical Analysis; Vol. 57; No. 6; 2519-2550; 10.1137/18M1194079
• Chen, Jiong and Budninskiy, Max, et el. (2019) Material-adapted refinable basis functions for elasticity simulation; ACM Transactions on Graphics; Vol. 38; No. 6; Art. No. 161; 10.1145/3355089.3356567
• Yoo, Gene Ryan and Owhadi, Houman (2019) De-noising by thresholding operator adapted wavelets; Statistics and Computing; Vol. 29; No. 6; 1185-1201; 10.1007/s11222-019-09893-x
• Owhadi, Houman and Scovel, Clint, et el. (2019) Kernel Mode Decomposition and programmable/interpretable regression networks; 10.48550/arXiv.1907.08592
• Zhang, Qingfu and Owhadi, Houman, et el. (2019) Multiresolution Operator Decomposition for Flow Simulation in Fractured Porous Media; Journal of Computational Physics; Vol. 391; 381-396; 10.1016/j.jcp.2018.12.032
• Owhadi, Houman and Yoo, Gene Ryan (2019) Kernel Flows: From learning kernels from data into the abyss; Journal of Computational Physics; Vol. 389; 22-47; 10.1016/j.jcp.2019.03.040
• Budninskiy, Max and Owhadi, Houman, et el. (2019) Operator-adapted wavelets for finite-element differential forms; Journal of Computational Physics; Vol. 388; 144-177; 10.1016/j.jcp.2019.02.018
• Campbell, Tom and Owhadi, Houman, et el. (2019) On testing the simulation theory; 10.48550/arXiv.1703.00058
• Owhadi, Houman and Scovel, Clint (2017) Qualitative Robustness in Bayesian Inference; ESAIM: Probability and Statistics; Vol. 21; 251-274; 10.1051/ps/2017014
• Owhadi, Houman and Zhang, Lei (2017) Gamblets for opening the complexity-bottleneck of implicit schemes for hyperbolic and parabolic ODEs/PDEs with rough coefficients; Journal of Computational Physics; Vol. 347; 99-128; 10.1016/j.jcp.2017.06.037
• Khoshnoud, Farbod and Esat, Ibrahim I., et el. (2017) Self-Powered Dynamic Systems in the Framework of Optimal Uncertainty Quantification; Journal of Dynamic Systems, Measurement, and Control; Vol. 139; No. 9; Art. No. 091005; 10.1115/1.4036367
• Owhadi, Houman and Scovel, Clint (2017) Universal Scalable Robust Solvers from Computational Information Games and fast eigenspace adapted Multiresolution Analysis; 10.48550/arXiv.1703.10761
• Owhadi, Houman and Scovel, Clint (2017) Toward Machine Wald; ISBN 978-3-319-12384-4; Handbook of Uncertainty Quantification; 157-191; 10.1007/978-3-319-12385-1_3
• Owhadi, Houman and Scovel, Clint (2017) Separability of reproducing kernel Hilbert spaces; Proceedings of the American Mathematical Society; Vol. 145; No. 5; 2131-2138; 10.1090/proc/13354
• Owhadi, Houman (2017) Multigrid with rough coefficients and Multiresolution operator decomposition from Hierarchical Information Games; SIAM Review; Vol. 59; No. 1; 99-149; 10.1137/15M1013894
• Owhadi, Houman (2017) The game theoretic approach to Uncertainty Quantification, reduced order modeling and numerical analysis; ISBN 9781624104527; AIAA SciTech Forum : 19th AIAA Non-Deterministic Approaches Conference; Art. No. 2017-1092; 10.2514/6.2017-1092
• Owhadi, Houman and Scovel, Clint (2017) Extreme points of a ball about a measure with finite support; Communications in Mathematical Sciences; Vol. 15; No. 1; 77-96; 10.4310/CMS.2017.v15.n1.a4
• Khoshnoud, Farbod and Esat, Ibrahim I., et el. (2016) Self-Powered and Bio-Inspired Dynamic Systems: Research and Education; ISBN 978-0-7918-5054-1; ASME 2016 International Mechanical Engineering Congress and Exposition; Art. No. V04AT05A046; 10.1115/IMECE2016-65276
• Tao, Molei and Owhadi, Houman, et el. (2016) Temperature and Friction Accelerated Sampling of Boltzmann-Gibbs Distribution; 10.48550/arXiv.1007.0995
• Bou-Rabee, Nawaf and Owhadi, Houman (2016) Stochastic Variational Partitioned Runge-Kutta Integrators for Constrained Systems; 10.48550/arXiv.0709.2222
• Owhadi, Houman and Scovel, Clint (2016) Brittleness of Bayesian inference and new Selberg formulas; 10.48550/arXiv.1304.7046
• Sullivan, T. J. and Owhadi, H. (2016) Equivalence of concentration inequalities for linear and non-linear functions; 10.48550/arXiv.1009.4913
• Bou-Rabee, Nawaf and Owhadi, Houman (2016) Ergodicity of Langevin Processes with Degenerate Diffusion in Momentums; 10.48550/arXiv.0710.4259
• Owhadi, Houman and Zhang, Lei (2016) Metric based up-scaling; 10.48550/arXiv.0505223
• Bou-Rabee, Nawaf and Owhadi, Houman (2016) Ballistic Transport at Uniform Temperature; 10.48550/arXiv.0710.1565
• Tao, Molei and Owhadi, Houman, et el. (2016) Structure preserving Stochastic Impulse Methods for stiff Langevin systems with a uniform global error of order 1 or 1/2 on position; 10.48550/arXiv.1006.4657
• McKerns, M. and Owhadi, H., et el. (2016) The optimal uncertainty algorithm in the mystic framework; 10.48550/arXiv.1202.1055
• Owhadi, Houman and Scovel, Clint (2016) Conditioning Gaussian measure on Hilbert space; 10.48550/arXiv.1506.04208
• Tao, Molei and Owhadi, Houman (2016) Variational and linearly implicit integrators, with applications; IMA Journal of Numerical Analysis; Vol. 36; No. 1; 80-107; 10.1093/imanum/dru064
• Ghanem, Roger and Higdon, David, et el. (2016) Introduction to Uncertainty Quantification; ISBN 978-3-319-11259-6; Handbook of Uncertainty Quantification; 1-4; 10.1007/978-3-319-11259-6_1-1
• Tao, Molei and Owhadi, Houman (2015) Temporal homogenization of linear ODEs, with applications to parametric super-resonance and energy harvest; Archive for Rational Mechanics and Analysis; Vol. 220; No. 1; 261-296; 10.1007/s00205-015-0932-4
• Han, Shuo and Tao, Molei, et el. (2015) Convex Optimal Uncertainty Quantification; SIAM Journal of Optimization; Vol. 25; No. 3; 1368-1387; 10.1137/13094712X
• Owhadi, Houman (2015) Bayesian Numerical Homogenization; Multiscale Modeling and Simulation; Vol. 13; No. 3; 812-828; 10.1137/140974596
• Owhadi, Houman and Scovel, Clint, et el. (2015) On the Brittleness of Bayesian Inference; SIAM Review; Vol. 57; No. 4; 566-582; 10.1137/130938633
• Owhadi, Houman and Scovel, Clint, et el. (2015) Brittleness of Bayesian inference under finite information in a continuous world; Electronic Journal of Statistics; Vol. 9; No. 1; 1-79; 10.1214/15-EJS989
• Kamga, P.-H. T. and Li, B., et el. (2014) Optimal uncertainty quantification with model uncertainty and legacy data; Journal of the Mechanics and Physics of Solids; Vol. 72; 1-19; 10.1016/j.jmps.2014.07.007
• Owhadi, Houman and Zhang, Lei, et el. (2014) Polyharmonic homogenization, rough polyharmonic splines and sparse super-localization; ESAIM-Mathematical Modelling and Numerical Analysis; Vol. 48; No. 2; 517-552; 10.1051/m2an/2013118
• Balarac, Guillaume and Owhadi, Houman (2014) Preface; ESAIM: Mathematical Modelling and Numerical Analysis; Vol. 48; No. 2; 305; 10.1051/m2an/2013108
• Sullivan, T. J. and McKerns, M., et el. (2013) Optimal Uncertainty Quantification for Legacy Data Observations of Lipschitz Functions; ESAIM-Mathematical Modelling and Numerical Analysis; Vol. 47; No. 6; 1657-1689; 10.1051/m2an/2013083
• Desbrun, Mathieu and Donaldson, Roger D., et el. (2013) Modeling Across Scales: Discrete Geometric Structures in Homogenization and Inverse Homogenization; ISBN 9783527671632; Multiscale Analysis and Nonlinear Dynamics; 19-64; 10.1002/9783527671632.ch02
• de Goes, Fernando and Alliez, Pierre, et el. (2013) On the equilibrium of simplicial masonry structures; ACM Transactions on Graphics; Vol. 32; No. 4; Art. No. 93; 10.1145/2461912.2461932
• Ober-Blöbaum, Sina and Tao, Molei, et el. (2013) Variational integrators for electric circuits; Journal of Computational Physics; Vol. 242; 498-530; 10.1016/j.jcp.2013.02.006
• Han, Shuo and Topcu, Ufuk, et el. (2013) Convex optimal uncertainty quantification: Algorithms and a case study in energy storage placement for power grids; ISBN 978-1-4799-0177-7; 2013 American Control Conference (ACC); 1130-1137
• Owhadi, H. and Scovel, C., et el. (2013) Optimal Uncertainty Quantification; SIAM Review; Vol. 55; No. 2; 271-345; 10.1137/10080782X
• Koon, Wang Sang and Owhadi, Houman, et el. (2013) Control of a model of DNA division via parametric resonance; Chaos; Vol. 23; No. 1; Art. No. 013117; 10.1063/1.4790835
• Kidane, A. and Lashgari, A., et el. (2012) Rigorous model-based uncertainty quantification with application to terminal ballistics, part I: Systems with controllable inputs and small scatter; Journal of the Mechanics and Physics of Solids; Vol. 60; No. 5; 983-1001; 10.1016/j.jmps.2011.12.001
• Adams, M. and Lashgari, A., et el. (2012) Rigorous model-based uncertainty quantification with application to terminal ballistics—Part II. Systems with uncontrollable inputs and large scatter; Journal of the Mechanics and Physics of Solids; Vol. 60; No. 5; 1002-1019; 10.1016/j.jmps.2011.12.002
• Owhadi, Houman and Zhang, Lei (2011) Localized Bases for Finite-Dimensional Homogenization Approximations with Nonseparated Scales and High Contrast; Multiscale Modeling and Simulation; Vol. 9; No. 4; 1373-1398; 10.1137/100813968
• Berlyand, Leonid and Owhadi, Houman (2011) Flux Norm Approach to Homogenization Problems with non-separated Scales; 10.7907/T5DC-SN48
• Desbrun, Mathieu and Donaldson, Roger D., et el. (2011) Discrete Geometric Structures in Homogenization and Inverse Homogenization with Application to EIT; 10.7907/XR8W-EA85
• Owhadi, Houman and Zhang, Lei (2011) Localized bases for finite dimensional homogenization approximations with non-separated scales and high-contrast
• Owhadi, H. and Scovel, C., et el. (2011) Optimal Uncertainty Quantification; 10.7907/TTW6-QD19
• Tao, Molei and Owhadi, Houman, et el. (2011) Non-intrusive and structure preserving multiscale integration of stiff ODEs, SDEs and Hamiltonian systems with hidden slow dynamics via flow averaging; 10.7907/QZNP-SR14
• Topcu, U. and Lucas, L. J., et el. (2011) Rigorous uncertainty quantification without integral testing; Reliability Engineering and System Safety; Vol. 96; No. 9; 1085-1091; 10.1016/j.ress.2010.07.013
• Doostan, Alireza and Owhadi, Houman (2011) A non-adapted sparse approximation of PDEs with stochastic inputs; Journal of Computational Physics; Vol. 230; No. 8; 3015-3034; 10.1016/j.jcp.2011.01.002
• Sullivan, T. J. and Topcu, U., et el. (2011) Uncertainty quantification via codimension-one partitioning; International Journal for Numerical Methods in Engineering; Vol. 85; No. 12; 1499-1521; 10.1002/nme.3030
• Tao, Molei and Owhadi, Houman, et el. (2011) Space-time FLAVORS: finite difference, multisymlectic, and pseudospectral integrators for multiscale PDEs; Dynamics of Partial Differential Equations; Vol. 8; No. 1; 21-45; 10.48550/arXiv.1104.0272
• Tao, Molei and Owhadi, Houman, et el. (2011) From efficient symplectic exponentiation of matrices to symplectic integration of high-dimensional Hamiltonian systems with slowly varying quadratic stiff potentials; Applied Mathematics Research eXpress; Vol. 2011; No. 2; 242-280; 10.1093/amrx/abr008
• Bayati, Basil and Owhadi, Houman, et el. (2010) A cutoff phenomenon in accelerated stochastic simulations of chemical kinetics via flow averaging (FLAVOR-SSA); Journal of Chemical Physics; Vol. 133; No. 24; Art. No. 244117; 10.1063/1.3518419
• Berlyand, Leonid and Owhadi, Houman (2010) Flux Norm Approach to Finite Dimensional Homogenization Approximations with Non-Separated Scales and High Contrast; Archive for Rational Mechanics and Analysis; Vol. 198; No. 2; 677-721; 10.1007/s00205-010-0302-1
• Tao, Molei and Owhadi, Houman, et el. (2010) Nonintrusive and Structure Preserving Multiscale Integration of Stiff ODEs, SDEs, and Hamiltonian Systems with Hidden Slow Dynamics via Flow Averaging; Multiscale Modeling and Simulation; Vol. 8; No. 4; 1269-1324; 10.1137/090771648
• Leyendecker, Sigrid and Lucas, Leonard J., et el. (2010) Optimal Control Strategies for Robust Certification; Journal of Computational and Nonlinear Dynamics; Vol. 5; No. 3; Art. No. 031008; 10.1115/1.4001375
• Sullivan, Timothy J. and McKerns, Mike, et el. (2010) Uncertainty quantification via codimension one domain partitioning and a new concentration inequality; Procedia - Social and Behavioral Sciences; Vol. 2; No. 6; 7751-7752; 10.1016/j.sbspro.2010.05.211
• Bou-Rabee, Nawaf and Owhadi, Houman (2010) Long-Run Accuracy of Variational Integrators in the Stochastic Context; SIAM Journal on Numerical Analysis; Vol. 48; No. 1; 278-297; 10.1137/090758842
• Zhang, Lei and Berlyand, Leonid, et el. (2010) Global Energy Matching Method for Atomistic-to-Continuum Modeling of Self-Assembling Biopolymer Aggregates; Multiscale Modeling & Simulation; Vol. 8; No. 5; 1958-1980; 10.1137/090781619
• Nair, Sujit and Chevva, Konda Reddy, et el. (2009) Multiple target detection using Bayesian learning; ISBN 978-1-4244-3871-6; Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference; 8549-8554; 10.1109/CDC.2009.5399565
• Kharevych, Lily and Mullen, Patrick, et el. (2009) Numerical coarsening of inhomogeneous elastic materials; ISBN 978-1-60558-726-4; SIGGRAPH '09 ACM SIGGRAPH 2009 papers; Art. No. 51; 10.1145/1576246.1531357
• Kharevych, Lily and Mullen, Patrick, et el. (2009) Numerical coarsening of inhomogeneous elastic materials; ACM Transactions on Graphics; Vol. 28; No. 3; Art. No. 51; 10.1145/1531326.1531357
• Bou-Rabee, Nawaf and Owhadi, Houman (2009) Stochastic variational integrators; IMA Journal of Numerical Analysis; Vol. 29; No. 2; 421-443; 10.1093/imanum/drn018
• Owhadi, Houman and Zhang, Lei (2008) Numerical homogenization of the acoustic wave equations with a continuum of scales; Computer Methods in Applied Mechanics and Engineering; Vol. 198; No. 3-4; 397-406; 10.1016/j.cma.2008.08.012
• Lucas, L. J. and Owhadi, H., et el. (2008) Rigorous verification, validation, uncertainty quantification and certification through concentration-of-measure inequalities; Computer Methods in Applied Mechanics and Engineering; Vol. 197; No. 51-52; 4591-4609; 10.1016/j.cma.2008.06.008
• Owhadi, Houman and Boulos, Areen (2008) Bistable Equilibrium Points of Mercury Body Burden; Journal of Biological Systems; Vol. 16; No. 1; 139-150; 10.1142/S0218339008002459
• Owhadi, Houman and Zhang, Lei (2007) Homogenization of Parabolic Equations with a Continuum of Space and Time Scales; SIAM Journal on Numerical Analysis; Vol. 46; No. 1; 1-36; 10.1137/060670420
• Owhadi, Houman (2004) From a market of dreamers to economical shocks; Physica A; Vol. 343; 583-602; 10.1016/j.physa.2004.05.078
• Owhadi, Houman (2004) Averaging Versus Chaos in Turbulent Transport?; Communications in Mathematical Physics; Vol. 247; No. 3; 553-599; 10.1007/s00220-004-1069-8
• Owhadi, Houman (2003) Anomalous slow diffusion from perpetual homogenization; Annals of Probability; Vol. 31; No. 4; 1935-1969; 10.1214/aop/1068646372
• Owhadi, Houman (2003) Approximation of the effective conductivity of ergodic media by periodization; Probability Theory and Related Fields; Vol. 125; No. 2; 225-258; 10.1007/s00440-002-0240-4
• Ben Arous, Gérard and Owhadi, Houman (2003) Multi-scale homogenization with bounded ratios and Anomalous Slow Diffusion; Communications on Pure and Applied Mathematics; Vol. 56; No. 1; 80-113; 10.1002/cpa.10053
• Ben Arous, Gérard and Owhadi, Houman (2002) Super-diffusivity in a shear flow model from perpetual homogenization; Communications in Mathematical Physics; Vol. 227; No. 2; 281-302; 10.1007/s002200200640
• Sullivan, Tim J. and Owhadi, Houman (2002) Distances and diameters in concentration inequalities: from geometry to optimal assignment of sampling resources; International Journal for Uncertainty Quantification; Vol. 2; No. 1; 21-38; 10.1615/Int.J.UncertaintyQuantification.2011003433