Homogenization of Parabolic Equations with a Continuum of Space and Time Scales. - Houman Owhadi; Lei Zhang 027 (SIAM J. Numer. Anal., 2007)

Multiple target detection using Bayesian learning. - Sujit Nair; Konda Reddy Chevva; Houman Owhadi; Jerrold E. Marsden (CDC, 2009)

Numerical coarsening of inhomogeneous elastic materials. - Liliya Kharevych; Patrick Mullen; Houman Owhadi; Mathieu Desbrun (ACM Trans. Graph., 2009)

Nonintrusive and Structure Preserving Multiscale Integration of Stiff ODEs, SDEs, and Hamiltonian Systems with Hidden Slow Dynamics via Flow Averaging. - Molei Tao; Houman Owhadi; Jerrold E. Marsden (Multiscale Model. Simul., 2010)

Global Energy Matching Method for Atomistic-to-Continuum Modeling of Self-Assembling Biopolymer Aggregates. - Lei Zhang 027; Leonid Berlyand; Maxim V. Fedorov; Houman Owhadi (Multiscale Model. Simul., 2010)

Long-Run Accuracy of Variational Integrators in the Stochastic Context. - Nawaf Bou-Rabee; Houman Owhadi (SIAM J. Numer. Anal., 2010)

A non-adapted sparse approximation of PDEs with stochastic inputs. - Alireza Doostan; Houman Owhadi (J. Comput. Phys., 2011)

Localized Bases for Finite-Dimensional Homogenization Approximations with Nonseparated Scales and High Contrast. - Houman Owhadi; Lei Zhang 027 (Multiscale Model. Simul., 2011)

Rigorous uncertainty quantification without integral testing. - Ufuk Topcu; Leonard J. Lucas; Houman Owhadi; Michael Ortiz (Reliab. Eng. Syst. Saf., 2011)

Optimal uncertainty quantification for legacy data observations of Lipschitz functions. - Timothy John Sullivan; Mike McKerns; Dominik Meyer; Florian Theil; Houman Owhadi; Michael Ortiz (CoRR, 2012)

The Optimal Uncertainty Algorithm in the Mystic Framework - Mike McKerns; Houman Owhadi; Clint Scovel; Timothy John Sullivan; Michael Ortiz (CoRR, 2012)

Convex optimal uncertainty quantification: Algorithms and a case study in energy storage placement for power grids. - Shuo Han 011; Ufuk Topcu; Molei Tao; Houman Owhadi; Richard M. Murray (ACC, 2013)

Variational integrators for electric circuits. - Sina Ober-Blöbaum; Molei Tao; Mulin Cheng; Houman Owhadi; Jerrold E. Marsden (J. Comput. Phys., 2013)

Optimal Uncertainty Quantification. - Houman Owhadi; Clint Scovel; Timothy John Sullivan; Mike McKerns; Michael Ortiz (SIAM Rev., 2013)

On the equilibrium of simplicial masonry structures. - Fernando de Goes; Pierre Alliez; Houman Owhadi; Mathieu Desbrun (ACM Trans. Graph., 2013)

Machine Wald. - Houman Owhadi; Clint Scovel (CoRR, 2015)

Bayesian Numerical Homogenization. - Houman Owhadi (Multiscale Model. Simul., 2015)

Convex Optimal Uncertainty Quantification. - Shuo Han 011; Molei Tao; Ufuk Topcu; Houman Owhadi; Richard M. Murray (SIAM J. Optim., 2015)

On the Brittleness of Bayesian Inference. - Houman Owhadi; Clint Scovel; Timothy John Sullivan (SIAM Rev., 2015)

Gamblets for opening the complexity-bottleneck of implicit schemes for hyperbolic and parabolic ODEs/PDEs with rough coefficients. - Houman Owhadi; Lei Zhang 027 (J. Comput. Phys., 2017)

Multigrid with Rough Coefficients and Multiresolution Operator Decomposition from Hierarchical Information Games. - Houman Owhadi (SIAM Rev., 2017)

Kernel Mode Decomposition and programmable/interpretable regression networks. - Houman Owhadi; Clint Scovel; Gene Ryan Yoo (CoRR, 2019)

Operator-adapted wavelets for finite-element differential forms. - Max Budninskiy; Houman Owhadi; Mathieu Desbrun (J. Comput. Phys., 2019)

Kernel Flows: From learning kernels from data into the abyss. - Houman Owhadi; Gene Ryan Yoo (J. Comput. Phys., 2019)

Multiresolution operator decomposition for flow simulation in fractured porous media. - Qingfu Zhang 002; Houman Owhadi; Jun Yao; Florian Schäfer 001; Zhaoqin Huang; Yang Li 011 (J. Comput. Phys., 2019)

De-noising by thresholding operator adapted wavelets. - Gene Ryan Yoo; Houman Owhadi (Stat. Comput., 2019)

Fast Eigenpairs Computation with Operator Adapted Wavelets and Hierarchical Subspace Correction. - Hehu Xie; Lei Zhang 027; Houman Owhadi (SIAM J. Numer. Anal., 2019)

Material-adapted refinable basis functions for elasticity simulation. - Jiong Chen 001; Max Budninskiy; Houman Owhadi; Hujun Bao; Jin Huang 001; Mathieu Desbrun (ACM Trans. Graph., 2019)

Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows. - Gene Ryan Yoo; Houman Owhadi (CoRR, 2020)

Competitive Mirror Descent. - Florian Schäfer 001; Anima Anandkumar; Houman Owhadi (CoRR, 2020)

Learning dynamical systems from data: a simple cross-validation perspective. - Boumediene Hamzi; Houman Owhadi (CoRR, 2020)

Do ideas have shape? Plato's theory of forms as the continuous limit of artificial neural networks. - Houman Owhadi (CoRR, 2020)

Decision Theoretic Bootstrapping. - Peyman Tavallali; Hamed Hamze Bajgiran; Danial J. Esaid; Houman Owhadi (CoRR, 2021)

Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball. - Hamed Hamze Bajgiran; Pau Batlle Franch; Houman Owhadi; Clint Scovel; Mahdy Shirdel; Michael Stanley; Peyman Tavallali (CoRR, 2021)

Computational Graph Completion. - Houman Owhadi (CoRR, 2021)

Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time Series. - Jonghyeon Lee; Edward De Brouwer; Boumediene Hamzi; Houman Owhadi (CoRR, 2021)

Solving and learning nonlinear PDEs with Gaussian processes. - Yifan Chen; Bamdad Hosseini; Houman Owhadi; Andrew M. Stuart (J. Comput. Phys., 2021)

Compression, Inversion, and Approximate PCA of Dense Kernel Matrices at Near-Linear Computational Complexity. - Florian Schäfer 001; Timothy John Sullivan; Houman Owhadi (Multiscale Model. Simul., 2021)

Consistency of empirical Bayes and kernel flow for hierarchical parameter estimation. - Yifan Chen; Houman Owhadi; Andrew M. Stuart (Math. Comput., 2021)

Sparse Cholesky Factorization by Kullback-Leibler Minimization. - Florian Schäfer 001; Matthias Katzfuss; Houman Owhadi (SIAM J. Sci. Comput., 2021)

Gaussian Process Hydrodynamics. - Houman Owhadi (CoRR, 2022)

One-Shot Learning of Stochastic Differential Equations with Computational Graph Completion. - Matthieu Darcy; Boumediene Hamzi; Giulia Livieri; Houman Owhadi; Peyman Tavallali (CoRR, 2022)

Multiclass classification utilising an estimated algorithmic probability prior. - Kamaludin Dingle; Pau Batlle; Houman Owhadi (CoRR, 2022)

Learning "best" kernels from data in Gaussian process regression. With application to aerodynamics. - Jean-Luc Akian; Luc Bonnet; Houman Owhadi; Éric Savin (J. Comput. Phys., 2022)

Uncertainty quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball. - Hamed Hamze Bajgiran; Pau Batlle; Houman Owhadi; Mostafa Samir; Clint Scovel; Mahdy Shirdel; Michael Stanley; Peyman Tavallali (J. Comput. Phys., 2022)

Learning Dynamical Systems from Data: A Simple Cross-Validation Perspective, Part V: Sparse Kernel Flows for 132 Chaotic Dynamical Systems. - Lu Yang; Xiuwen Sun; Boumediene Hamzi; Houman Owhadi; Naiming Xie (CoRR, 2023)

Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes. - Yifan Chen; Houman Owhadi; Florian Schäfer 001 (CoRR, 2023)

A Mini-Batch Method for Solving Nonlinear PDEs with Gaussian Processes. - Xianjin Yang; Houman Owhadi (CoRR, 2023)

Sparse Cholesky factorization by greedy conditional selection. - Stephen Huan; Joseph Guinness; Matthias Katzfuss; Houman Owhadi; Florian Schäfer 001 (CoRR, 2023)

Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning. - Boumediene Hamzi; Marcus Hutter; Houman Owhadi (CoRR, 2023)

Computational Hypergraph Discovery, a Gaussian Process framework for connecting the dots. - Théo Bourdais; Pau Batlle; Xianjin Yang; Ricardo Baptista; Nicolas Rouquette; Houman Owhadi (CoRR, 2023)

Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach. - Daniel Lengyel; Panos Parpas; Boumediene Hamzi; Houman Owhadi (CoRR, 2024)

Operator Learning with Gaussian Processes. - Carlos Mora; Amin Yousefpour; Shirin Hosseinmardi; Houman Owhadi; Ramin Bostanabad (CoRR, 2024)

Model aggregation: minimizing empirical variance outperforms minimizing empirical error. - Théo Bourdais; Houman Owhadi (CoRR, 2024)

Toward Efficient Kernel-Based Solvers for Nonlinear PDEs. - Zhitong Xu; Da Long; Yiming Xu; Guang Yang; Shandian Zhe; Houman Owhadi (CoRR, 2024)

Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator. - Jonghyeon Lee; Boumediene Hamzi; Boya Hou; Houman Owhadi; Gabriele Santin; Umesh Vaidya (CoRR, 2024)

Kolmogorov n-widths for multitask physics-informed machine learning (PIML) methods: Towards robust metrics. - Michael Penwarden; Houman Owhadi; Robert M. Kirby (Neural Networks, 2024)

Sparse Recovery of Elliptic Solvers from Matrix-Vector Products. - Florian Schäfer 001; Houman Owhadi (SIAM J. Sci. Comput., 2024)

Kernel methods are competitive for operator learning. - Pau Batlle; Matthieu Darcy; Bamdad Hosseini; Houman Owhadi (J. Comput. Phys., 2024)

Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models. - Théo Bourdais; Houman Owhadi (ICLR, 2025)

Error analysis of kernel/GP methods for nonlinear and parametric PDEs. - Pau Batlle; Yifan Chen; Bamdad Hosseini; Houman Owhadi; Andrew M. Stuart (J. Comput. Phys., 2025)

Diffeomorphic Measure Matching with Kernels for Generative Modeling. - Biraj Pandey; Bamdad Hosseini; Pau Batlle; Houman Owhadi (SIAM J. Math. Data Sci., 2025)

Solving Roughly Forced Nonlinear PDEs via Misspecified Kernel Methods and Neural Networks. - Ricardo Baptista; Edoardo Calvello; Matthieu Darcy; Houman Owhadi; Andrew M. Stuart; Xianjin Yang (CoRR, 2025)

Gaussian measures conditioned on nonlinear observations: consistency, MAP estimators, and simulation. - Yifan Chen; Bamdad Hosseini; Houman Owhadi; Andrew M. Stuart (Stat. Comput., 2025)

Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis. - Yasamin Jalalian; Juan Felipe Osorio Ramirez; Alexander Hsu; Bamdad Hosseini; Houman Owhadi (CoRR, 2025)

Pruning Deep Neural Networks via a Combination of the Marchenko-Pastur Distribution and Regularization. - Leonid Berlyand; Théo Bourdais; Houman Owhadi; Yitzchak Shmalo (CoRR, 2025)

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs. - Adrienne M. Propp; Jonas A. Actor; Elise Walker; Houman Owhadi; Nathaniel Trask; Daniel M. Tartakovsky (CoRR, 2025)

Discovering Algorithms with Computational Language Processing. - Théo Bourdais; Abeynaya Gnanasekaran; Houman Owhadi; Tuhin Sahai (CoRR, 2025)