Books

1. Springer Handbook of Uncertainty Quantification, R. Ghanem, D. Higdon and H. Owhadi (Eds.), 2016 [ link ] 2. Operator adapted wavelets, fast solvers, and numerical homogenization from a game theoretic approach to numerical approximation and algorithm design. H. Owhadi and C. Scovel. Cambridge University Press, Cambridge Monographs on Applied and Computational Mathematics, 2019 [link] 3. Kernel Mode Decomposition and the programming of kernels. H. Owhadi, C. Scovel and G. R. Yoo. Springer 2021 [link] [Back cover] [arXiv:1907.08592] (early version) [Python source codes]

Selected preprints

1. Gaussian Measures Conditioned on Nonlinear Observations: Consistency, MAP Estimators, and Simulation. Yifan Chen, Bamdad Hosseini, Houman Owhadi, Andrew M Stuart. 2024. [ arXiv:2405.13149 ] 2. Optimization-based frequentist confidence intervals for functionals in constrained inverse problems: Resolving the Burrus conjecture. 2023. Pau Batlle, Pratik Patil, Michael Stanley, Houman Owhadi, Mikael Kuusela [ arXiv:2310.02461 ] 3. Diffeomorphic Measure Matching with Kernels for Generative Modeling. 2024 B Pandey, B Hosseini, P Batlle, H Owhadi [ arXiv:2402.08077 ] 4. Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs. 2023. Pau Batlle, Yifan Chen, Bamdad Hosseini, Houman Owhadi, Andrew M Stuart [ arXiv:2305.04962 ]

Refereed Journal Publications

1. Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots. Théo Bourdais, Pau Batlle, Xianjin Yang, Ricardo Baptista, Nicolas Rouquette, Houman Owhadi. Proceedings of the National Academy of Sciences, vol 121, no 32, pages e2403449121, 2024. [ paper ] [ Supporting Information ] [ Code ] [ Blog post ] 2. Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes. Yifan Chen, Houman Owhadi, Florian Schäfer Mathematics of Computation. 2024 [ arXiv:2304.01294 ] 3. Sparse recovery of elliptic solvers from matrix-vector products F. Schäfer, H. Owhadi SIAM Journal on Scientific Computing 46 (2), A998-A1025. 2024 [arXiv:2110.05351] 4. Learning Dynamical Systems from Data: A Simple Cross-Validation Perspective, Part V: Sparse Kernel Flows for 132 Chaotic Dynamical Systems, 2023 L Yang, X Sun, B Hamzi, H Owhadi, N Xie Physica D: Nonlinear Phenomena, 134070, 6, 2024 [ arXiv:2301.10321 ] 5. Hausdorff metric based training of kernels to learn attractors with application to 133 chaotic dynamical systems. Lu Yang, Boumediene Hamzi, Yannis Kevrekidis, Houman Owhadi, Xiuwen Sun, Naiming Xie. Physica D: Nonlinear Phenomena. Volume 466, October 2024, 134192 6. Forward Model Emulator for Atmospheric Radiative Transfer Using Gaussian Processes And Cross Validation OM Lamminpää, JI Susiluoto, JM Hobbs, JL McDuffie, AJ Braverman, H Owhadi Atmospheric Measurement Techniques Discussions 2024, 1-32 [ pdf ] 7. Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning. Boumediene Hamzi, Marcus Hutter, Houman Owhadi Physica D: Nonlinear Phenomena, 2024, 134153. 8. Decision Theoretic Bootstrapping P Tavallali, HH Bajgiran, DJ Esaid, H Owhadi International Journal for Uncertainty Quantification 14 (4). 2024 9. Kernel Methods are Competitive for Operator Learning. Pau Batlle, Matthieu Darcy, Bamdad Hosseini, Houman Owhadi Journal of Computational Physics, Volume 496, 2024, 112549 [ arXiv:2304.13202 ] 10. Gaussian process hydrodynamics. H Owhadi. Applied Mathematics and Mechanics (English Edition). volume 44, pages 1175-1198, 2023. [ arXiv:2209.10707 ] 11. Do ideas have shape? Idea registration as the continuous limit of artificial neural networks. Physica D: Nonlinear Phenomena 444, 133592, 2023. H. Owhadi [arXiv:2008.03920] [Fields Institute talk] [ slides ] 12. Multiclass classification utilising an estimated algorithmic probability prior, 2023 Physica D: Nonlinear Phenomena 448, 133713 K Dingle, P Batlle, H Owhadi [ arXiv:2212.07426 ] 13. Learning dynamical systems from data: A simple cross-validation perspective, part iii: Irregularly-sampled time series Physica D: Nonlinear Phenomena. Volume 443, January 2023, 133546 J Lee, E De Brouwer, B Hamzi, H Owhadi [ arXiv:2111.13037 ] 14. One-shot learning of stochastic differential equations with data adapted kernels M Darcy, B Hamzi, G Livieri, H Owhadi, P Tavallali Physica D: Nonlinear Phenomena 444, 133583, 2023 [ pdf ] 15. Learning" best" kernels from data in Gaussian process regression. With application to aerodynamics. JL Akian, L Bonnet, H Owhadi, E Savin Journal of Computational Physics 470, 111595, 2022 [ arXiv:2206.02563 ] 16. Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball. Hamed Hamze Bajgiran, Pau Batlle Franch, Houman Owhadi, Mosatafa Samir, Clint Scovel, Mahdy Shirdel, Michael Stanley, Peyman Tavallali. Journal of Computational Physics 471, 111608, 2022 [arXiv:2108.10517, 2021] [slides] 17. Computational Graph Completion. Research in the Mathematical Sciences 9 (2), 27 (2022) H. Owhadi [ arXiv:2110.10323 , Oct 2021] 18. Mean-field limits of trained weights in deep learning: A dynamical systems perspective. Dolomites Research Notes on Approximation 15 (3) 2022 A Smirnov, B Hamzi, H Owhadi 19. Solving and Learning Nonlinear PDEs with Gaussian Processes. Journal of Computational Physics, Volume 447, 15 December 2021, 110668 Y. Chen, B. Hosseini, H. Owhadi, AM. Stuart [arXiv:2103.12959] [slides] [pdf] 20. Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methods. Proceedings of the Royal Society A. 2021 B. Hamzi, R. Maulik, H. Owhadi [arXiv:2103.10935] [pdf] 21. Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows. Physica D: Nonlinear Phenomena, Volume 426, 15 November 2021, 132952 G. R. Yoo and H. Owhadi [arXiv:2002.08335] 22. Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation. Mathematics of Computation, 2021. Y. Chen, H. Owhadi, A. M. Stuart [arXiv:2005.11375] 23. Sparse Cholesky factorization by Kullback-Leibler minimization. 2020. F. Schäfer, M. Katzfuss and H. Owhadi SIAM SISC, 2021 [arXiv:2004.14455] [Julia source codes] [Talk] 24. Learning dynamical systems from data: a simple cross-validation perspective, part I: Parametric kernel flows. B. Hamzi and H. Owhadi Physica D: Nonlinear Phenomena, Volume 421, 2021 [arXiv:2007.05074][pdf] 25. Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity. 2017. F. Schäfer, T. J. Sullivan and H. Owhadi. SIAM MMS, 2021 [ arXiv:1706.02205 ] [Julia souce codes] [Blog] [Talk] 26. Statistical Numerical Approximation. H. Owhadi, C. Scovel and F. Schäfer. Notices of the American Mathematical Society, volume 66, number 10, featured article, pages 1608-1617. 2019. [pdf] 27. Material-adapted Refinable Basis Functions for Elasticity Simulation Jiong Chen, Max Budninskiy, Houman Owhadi, Hujun Bao, Jin Huang, and Mathieu Desbrun. ACM Trans. Graph. (SIGGRAPH Asia), 38(6), Art. 161, 2019. [pdf] 28. Fast eigenpairs computation with operator adapted wavelets and hierarchical subspace correction. H. Xie, L. Zhang and H. Owhadi, SIAM Journal on Numerical Analysis, 2019. [arXiv:1806.00565] 29. Kernel Flows: from learning kernels from data into the abyss. H. Owhadi, G. R. Yoo, Journal of Computational Physics, volume 389, Pages 22-47, 2019. [ pdf ] [arXiv:1808.04475] Youtube Playlist 30. Operator-adapted wavelets for finite-element differential forms. M. Budninskiy, H. Owhadi, M. Desbrun, Journal of Computational Physics, Volume 388, 1 July 2019, Pages 144-177, 2019. 31. De-noising by thresholding operator adapted wavelets. G. R. Yoo and H. Owhadi, Statistics and Computing, volume 29, number 6, 1185--1201, 2019. [arXiv:1805.10736] 32. Conditioning Gaussian measure on Hilbert space. H. Owhadi and C. Scovel. Journal of Mathematical and Statistical Analysis, 2018. [ arXiv:1506.04208 ] 33. Qualitative Robustness in Bayesian Inference. H. Owhadi and C. Scovel. ESAIM: Probability and Statistics, 2017. [ arXiv:1411.3984 ] 34. Gamblets for opening the complexity-bottleneck of implicit schemes for hyperbolic and parabolic ODEs/PDEs with rough coefficients. H. Owhadi and Lei Zhang. Journal of Computational Physics, Volume 347, pages 99-128, 2017. [ pdf | arXiv:1606.07686 ] 35. On testing the simulation theory. T. Campbell, H. Owhadi, J. Sauvageau and D. Watkinson. International Journal of Quantum Foundations. Volume 3, Issue 3, pages 78-99, 2017. [ pdf | arXiv:1703.00058 ] 36. Separability of reproducing kernel spaces. H. Owhadi and C. Scovel. Proceedings of the AMS. Volume 145, Number 5, Pages 2131–2138, 2017. [ pdf | arXiv:1506.04288 ] 37. Extreme points of a ball about a measure with finite support. H. Owhadi and C. Scovel. Communications in Mathematical Sciences. Vol. 15, No. 1, pp. 77-96, 2017. [ pdf | arXiv:1504.06745 ] 38. Multigrid with rough coefficients and Multiresolution operator decomposition from Hierarchical Information Games. SIAM Review (Research spotlights), 59(1), 99–149, 2017. [ pdf | arXiv:1503.03467 ] Presentation: [ video | slides ] 39. Energy harvest via parametric super-resonance and temporal homogenization of linear ODEs. M. Tao and H. Owhadi. Archives for Rational Mechanics and Analysis, Volume 220, Issue 1, pp 261-296, 2016. [ pdf | arXiv:1310.6460 ] 40. Brittleness of Bayesian inference and new Selberg formulas. H. Owhadi and C. Scovel. Communications in Mathematical Sciences, vol. 14, n. 1, pp. 83-145, 2016. [ pdf | arXiv:1304.7046 ] Presentation: [ slides | slides ] 41. Variational and linearly-implicit integrators, with applications. M. Tao and H. Owhadi. IMA J. Numer. Anal, 36 , no. 1, pp. 80–107, 2016. [ pdf | arXiv:1103.4645 ] 42. Bayesian Numerical Homogenization. H. Owhadi. SIAM Multiscale Modeling & Simulation, 13, no. 3, pp. 812–828, 2015. [ pdf | arXiv:1406.6668 ] Presentation: [ slides ] 43. On the Brittleness of Bayesian Inference. H. Owhadi, C. Scovel and T. Sullivan. SIAM Review (Research spotlights), 57(4), 566-582, 2015. [ pdf | arXiv:1308.6306 | blog 1 | blog 2 ] Presentation: [ slides ] 44. Convex Optimal Uncertainty Quantification. S. Han, M. Tao, U. Topcu, H. Owhadi and Richard M. Murray. SIAM Journal on Optimization, vol. 25, issue 23, pp. 1368-1387, 2015. [ pdf | arXiv:1311.7130 ] 45. Brittleness of Bayesian Inference under Finite Information in a Continuous World. H. Owhadi, C. Scovel and T. Sullivan. Electronic Journal of Statistics, vol 9, pp 1-79, 2015. [ pdf | arXiv:1304.6772 | blog ] Presentation: [ slides ] 46. Polyharmonic homogenization, rough polyharmonic splines and sparse super-localization. H. Owhadi, L. Zhang and L. Berlyand. ESAIM: Mathematical Modeling and Numerical Analysis. 48, PP. 517–552, 2014. [ pdf | arXiv:1212.0812 ] 47. On the Equilibrium of Simplicial Masonry Structures. F. de Goes, P. Alliez, H. Owhadi and M. Desbrun. ACM Transactions on Graphics (SIGGRAPH) 32(4), 2013. [ pdf ] 48. Optimal uncertainty quantification for legacy data observations of Lipschitz functions. T. J. Sullivan, M. McKerns, D. Meyer, F. Theil, H. Owhadi and M. Ortiz ESAIM: Mathematical Modelling and Numerical Analysis (M2AN). Volume 47, Issue 6, pp 1657-1689, 2013. [ pdf | arxiv:1202.1928 ] 49. Variational integrators for electric circuits. S. Ober-Blobaum, M. Tao, M. Cheng, H. Owhadi and J. E. Marsden. Journal of Computational Physics, vol. 242, issue 1, pp. 498–530, 2013. [ pdf | arXiv:1103.1859 ] 50. Control of a Model of DNA Division via Parametric Resonance. W. S. Koon, H. Owhadi, M. Tao and T. Yanao. Chaos, 23, 013117, 2013. [ pdf | arXiv:1211.4064 ] 51. Optimal Uncertainty Quantification. H. Owhadi, C. Scovel, T. Sullivan, M. McKerns and M. Ortiz. SIAM Review (Expository Research Papers), vol. 55, no. 2 : pp. 271-345, 2013. [ pdf | arXiv:1009.0679 ] Minitutorial: [ slides ] 52. Distances and diameters in concentration inequalities: From geometry to optimal assignment of sampling resource function. T. Sullivan and H. Owhadi. International Journal for Uncertainty Quantification, 2 (1), 2012. [ pdf ] 53. Rigorous model-based uncertainty quantification with application to terminal ballistics, part I: Systems with controllable inputs and small scatter. A.A Kidane, A. Lashgari, B. Li, M. McKerns, M. Ortiz, H. Owhadi, G. Ravichandran, M. Stalzer, and T. J. Sullivan. Journal of the Mechanics and Physics of Solids. 60 (5) 983–1001, 2012. [ pdf ] 54. Rigorous model-based uncertainty quantification with application to terminal ballistics, part II: Systems with uncontrollable inputs and large scatter. M. Adams, A. Lashgari, B. Li, M. McKerns, J. Mihaly, M. Ortiz, H. Owhadi, A. J. Rosakis, M. Stalzer, and T. J. Sullivan. Journal of the Mechanics and Physics of Solids. 60 (5) 1002–1019, 2012. [ pdf ] 55. Localized bases for finite dimensional homogenization approximations with non-separated scales and high-contrast. H. Owhadi and L. Zhang. SIAM Multiscale Modeling & Simulation, 9, pp. 1373-1398, 2011. [ pdf | arXiv:1011.0986 ] 56. From efficient symplectic exponentiation of matrices to symplectic integration of high-dimensional Hamiltonian systems with slowly varying quadratic stiff potentials. M. Tao, H. Owhadi and J. Marsden. Applied Mathematics Research Express, vol. 2, pp. 242-280, 2011. [ pdf | arXiv:1006.4659 ] 57. Space-time FLAVORS: finite difference, multisymlectic, and pseudospectral integrators for multiscale PDEs. M. Tao, H. Owhadi and J. Marsden. Dynamics of Partial Differential Equations. vol. 8, no. 1, pp. 21-45, 2011. [ pdf | arXiv:1104.0272 ] 58. A non-adapted sparse approximation of PDEs with stochastic inputs. A. Doostan and H. Owhadi. Journal of Computational Physics. vol. 230, no. 8, pp. 3015-3034, 2011. [ pdf ] 59. A Cutoff Phenomenon in Accelerated Stochastic Simulations of Chemical Kinetics via Flow Averaging (FLAVOR-SSA). B. Bayati, H. Owhadi and P. Koumoutsakos. Journal of Chemical Physics. vol. 133, no. 24, 2010. [ pdf ] 60. Rigorous Uncertainty Quantification without Integral Testing. U. Topcu, L. J. Lucas, H. Owhadi and M. Ortiz. Reliability Engineering and System Safety. 96: 1085-1091, 2011. [ pdf ] 61. Stochastic simulation of extracting energy with an optically controlled nano-electromechanical engine. F. Khoshnoud, H. Owhadi and C. de Silva. International Journal of Modelling and Simulation, vol. 3, no. 2, 2011. 62. Uncertainty Quantification via co-dimension one partitioning. T. Sullivan, U. Topcu, M. McKerns and H. Owhadi. Journal for Numerical Methods in Engineering. vol. 85, issue 12, pp.1499–1521, 2011. [ pdf ] 63. Global Energy Matching Method for Atomistic to Continuum Modeling of Self-Assembling Biopolymer Aggregates. L. Zhang, L. Berlyand, M. Fedorov and H. Owhadi. SIAM Multiscale Modeling & Simulation, Volume 8, Issue 5, pp. 1958-1980, 2010. [ pdf ] 64. Non-intrusive and structure preserving multiscale integration of stiff ODEs, SDEs and Hamiltonian systems with hidden slow dynamics via flow averaging. M. Tao, H. Owhadi and J. E. Marsden. SIAM Multiscale Modeling & Simulation, vol.8, no. 4, pp. 269-1324, 2010. [ pdf | arXiv: 0908.1241 ] Presentation: [ slides ] 65. Flux norm approach to finite dimensional homogenization approximations with non-separated scales and high contrast. L. Berlyand and H. Owhadi. Archives for Rational Mechanics and Analysis, vol. 198, no. 2, pp. 677-721, 2010. [ pdf | arXiv: 0901.1463 ] 66. Numerical Coarsening of Inhomogeneous Linear Elastic Materials. L. Kharevych, P. Mullen, H. Owhadi and M. Desbrun. ACM Transactions on Graphics (SIGGRAPH), 28(3), 2009. [ pdf ] 67. Long-Run Behavior of Variational Integrators in the Stochastic Context. N. Bou-Rabee and H. Owhadi. SIAM Journal of Numerical Analysis, 48, 278-297, 2010. [ pdf ] 68. Optimal Control Strategies for Robust Certification. S. Leyendecker, L. J. Lucas, H. Owhadi and M. Ortiz. ASME J. Comput. Nonlinear Dynam, vol. 5, issue 3, 2010. 69. Stochastic Variational Integrators. N. Bou-Rabee and H. Owhadi. IMA Journal of Numerical Analysis, vol. 29, pp. 421-443, 2009. Editor's Choice Article, top 5 most downloaded articles in IMA Journal of Numerical Analysis. [ pdf | arXiv: 0708.2187 ] 70. Rigorous Verification, Validation, Uncertainty Quantification and Certification through Concentration-of-Measure Inequalities. L. J. Lucas, H. Owhadi and M. Ortiz. Computer Methods in Applied Mechanics and Engineering, vol. 197, pp. 4591--4609, 2008. [ pdf ] 71. Ergodicity for Langevin Processes with Degenerate Diffusion in Momentums. N. Bou-Rabee and H. Owhadi. International Journal of Pure and Applied Mathematics, vol. 45, no. 3, pp. 475-490, 2008. [ pdf | arXiv: 0710.4259 ] 72. Bistable equilibrium points of mercury body burden. H. Owhadi and A. Boulos. Journal of Biological Systems, vol. 16, no. 1, 2008. [ arXiv:q-bio/0606024 ] 73. Homogenization of the acoustic wave equation with a continuum of scales. H. Owhadi and L. Zhang. Computer Methods in Applied Mechanics and Engineering, vol. 198, no. 3-4, pp. 397-406, 2008. [ pdf | arXiv: math/0604380 ] Presentation: [ slides | ppt (with embedded videos) ] 74. Homogenization of Parabolic equations with a continuum of space and time scales. H. Owhadi and L. Zhang. SIAM J. Numer. Anal. 46 (2007/08), no. 1, 1--36. [ pdf | arxiv: 0512504 ] Presentation: [ slides | ppt (with embedded videos) ] 75. Metric Based Up-scaling. H. Owhadi and L. Zhang. Communications on Pure and Applied Mathematics, vol. LX, pp. 0675–0723, 2007. [ pdf | arXiv: math/0505223 ] Presentation: [ slides | ppt (with embedded videos) ] 76. From a Market of Dreamers to Economical Shocks. H. Owhadi. Physica A, vol. 343, pp. 583-602, 2004. [ pdf ] 77. Averaging versus Chaos in Turbulent Transport? H. Owhadi. Communications in Mathematical Physics, vol. 247, no. 3, pp. 553--599, 2004. [ pdf | arXiv:math-ph/0402028 ] Presentation: [ slides ] 78. Approximation of the effective conductivity of ergodic media by periodization. H. Owhadi. Probability Theory and Related Fields. 125, 225-258, 2003. [ pdf | arXiv:math/0201062 ] 79. Multi-scale homogenization with bounded ratios and Anomalous Slow Diffusion. G. Ben Arous and H. Owhadi. Communications on Pure and Applied Mathematics, vol. XVI, pp. 80-113, 2003. [ pdf | arXiv:math/0105258 ] 80. Anomalous Slow Diffusion from Perpetual Homogenization on infinitely many scales. H. Owhadi. Annals of Probability, vol. 31, No. 4 - October 2003. [ pdf | arXiv:math/0105165 ] 81. Super-diffusivity in a shear flow model from perpetual homogenization. G. Ben Arous and H. Owhadi. Communications in Mathematical Physics, vol. 22, no. 2, pp. 281--302, 2002. [ pdf | arXiv:math/0105199 ] 82. Isolation of 10 differentially expressed cDNAsin p53-induced apoptosis: Activation of the vertebrate homologue of the Drosophila seven in absentia gene. R. B. Amson, M. Nemani, J.-P. Roperch, D. Israeli, L. Bougueleret, I. Legall, M. Medhioub, G. Linares-Cruz, F. Lethrosne, P. Pasturaud, L. Piouffre, S. Pieur, L. Susini, V. Alvaro, P. Millasseau, C. Guidicelli, H. Bui, C. Massart, L. Cazes, F. Dufour, H. Bruzzoni-Giovanelli, H. Owhadi, C . Hennion, G. Charpak, J. Dausset, F. Calvo, M. Oren, D. Cohen and A. Telerman. Proceedings of the National Academy of Sciences USA, vol. 93, issue 9, pp. 3953-3957, 1996. [ pdf ]

Other preprints

1. Can Specific THz Fields Induce Collective Base-Flipping in DNA? A Stochastic Averaging and Resonant Enhancement Investigation Based on a New Mesoscopic Model. Wang Sang Koon, Houman Owhadi, Molei Tao, Tomohiro Yanao. 2024 [ arXiv:2406.15354 ] 2. Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems rom Data: A global optimization approach. Daniel Lengyel, Panos Parpas, Boumediene Hamzi, Houman Owhadi. 2024. [ arXiv:2408.06465 ] 3. Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics. 2024. M Penwarden, H Owhadi, RM Kirby [ arXiv:2402.11126 ] 4. A Mini-Batch Method for Solving Nonlinear PDEs with Gaussian Processes. 2023. Xianjin Yang, Houman Owhadi. [ arXiv:2306.00307 ]. 5. Learning dynamical systems from data: a simple cross-validation perspective, part II: nonparametric kernel flows, 2021. M Darcy, B Hamzi, J Susiluoto, A Braverman, H Owhadi [pdf] 6. Aggregation of Pareto optimal models. 2021. Hamed Hamze Bajgiran, Houman Owhadi [arXiv:2112.04161] 7. Aggregation of Models, Choices, Beliefs, and Preferences. 2021. Hamed Hamze Bajgiran, Houman Owhadi [arXiv:2111.11630] 8. Competitive Mirror Descent, 2020 F. Schäfer, A. Anandkumar, H. Owhadi [arXiv:2006.10179] [GitHub] [ICML spotlight talk]

Book Chapters

1. Toward Machine Wald. H. Owhadi and C. Scovel. Springer Handbook of Uncertainty Quantification, pp 1-35, 2016, [ pdf | arXiv:1508.02449 ] 2. Modeling Across Scales: Discrete Geometric Structures in Homogenization and Inverse Homogenization. M. Desbrun, R. Donaldson and H. Owhadi, Reviews of Nonlinear Dynamics and Complexity (Wiley). Special issue on Multiscale Analysis and Nonlinear Dynamics. 2012. [ pdf ] Presentation: [ slides | ppt (with embedded videos) ]

Conference Publications

1. Radiative transfer emulation for hyperspectral imaging retrievals with advanced kernel flows-based gaussian process emulation AGU Fall Meeting Abstracts 2021, NG25A-0506, 2021 Jouni Susiluoto, Amy Braverman, Philip Brodrick, Boumediene Hamzi, Maggie Johnson, Otto Lamminpaa, Houman Owhadi, Clint Scovel, Joaquim Teixeira, Michael Turmon 2. Kernel flows to infer the structure of convective storms from satellite passive microwave observations AGU Fall Meeting Abstracts 2021, A55F-1445, 2021 Sai Prasanth, Ziad Haddad, Jouni Susiluoto, Amy Braverman, Houman Owhadi, Boumediene Hamzi, Svetla Hristova-Veleva, Joseph Turk 3. The game theoretic approach to Uncertainty Quantification, reduced order modeling and numerical analysis. H. Owhadi. 19th AIAA Non-Deterministic Approaches Conference Grapevine, Texas, 2017. [ pdf ] 4. Convex optimal uncertainty quantification: Algorithms and a case study in energy storage placement for power grids. S. Han, U. Topcu, M. Tao, H. Owhadi and R. M. Murray. American Control Conference (ACC), 2013. [ pdf ] 5. Optimal Uncertainty Quantification. M. Ortiz, H. Owhadi, M. McKerns, T. J. Sullivan and C. Scovel. In Advanced Computational Engineering.12–18 February 2012, ed. O. Allix, C. Carstensen, J. Schröder & P. Wriggers. 6. Variational integrators for electric circuits. S. Ober-Blöbaum, M. Tao and H. Owhadi. Special Issue: Proceedings in Applied Mathematics and Mechanics. vol. 11, issue 1, pp. 783–784, 2011. [ pdf ] 7. Uncertainty quantification via codimension-one domain partitioning and a new concentration inequality. T. J. Sullivan, U. Topcu, M. McKerns and H. Owhadi. Social and Behavioral Sciences, vol. 2, no. 6, pp. 7751–7752, 2010. 8. Stochastic Simulation of a Casimir Oscillator. F. Khoshnoud, H. Owhadi and C. W. de Silva. IMECE 2010. 9. Analysis and Design of a Nano-electromechanical Vibration Sensor. F. Khoshnoud, C. W. de Silva and H. Owhadi. IMECE 2010. 10. Multiple target detection using bayesian learning. S. Nair, K. Reddy, H. Owhadi and J. E. Marsden. In Proc. IEEE Conf. Decision and Control, Shanghai, December 2009. 11. Super-diffusion and its collapse in a quenched multi-scale passive transport model. H. Owhadi. ICMP 2003 proceedings.

Technical Reports

1. “What is UQ?” C. Scovel, H. Owhadi. T. J. Sullivan, M. McKerns & M. Ortiz ADTSC Science Highlights 2012, Los Alamos National Laboratory, LA-UR 12-20429:26–27, 2012. [ pdf ] 2. The optimal uncertainty algorithm in the mystic framework. M. McKerns, H. Owhadi, C. Scovel, T. J. Sullivan and M. Ortiz. Caltech CACR Technical Report, no. 523, 2010. [ arxiv: 1202.1055 ] 3. Universal Scalable Robust Solvers from Computational Information Games and fast eigenspace adapted Multiresolution Analysis. H. Owhadi and C. Scovel. 2017. [ arXiv:1703.10761 ] Minitutorial: [ Part I | Part II | Part III ] Lead to this book 4. Notes on operator valued kernels, feature maps and Gaussian processes. H. Owhadi. Oct 2021. [ pdf ]

Thesis

1. PhD Dissertation : Anomalous diffusion and homogenization on an infinite number of scales. EPFL (January 2001). Thesis number 2340. [ pdf ]