Clayton G. Webster

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 31

Top Topics

Image Inpainting

Numerical Analysis

Ambrosio Tortorelli

Top Venues

SIAM/ASA J. Uncertain. Quantification

Comput. Math. Appl.

Int. J. Comput. Math.

Publications

Andrew Starnes, Anton Dereventsov, Clayton G. Webster
Increasing Entropy to Boost Policy Gradient Performance on Personalization Tasks. ICDM (Workshops) (2023)
Andrew Starnes, Anton Dereventsov, Clayton G. Webster
Increasing Entropy to Boost Policy Gradient Performance on Personalization Tasks. CoRR (2023)
Anton Dereventsov, Andrew Starnes, Clayton G. Webster
Examining Policy Entropy of Reinforcement Learning Agents for Personalization Tasks. CoRR (2022)
Anton Dereventsov, Joseph D. Daws Jr., Clayton G. Webster
Offline Policy Comparison under Limited Historical Agent-Environment Interactions. CoRR (2021)
Anton Dereventsov, Ranga Raju Vatsavai, Clayton G. Webster
On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks. CoRR (2021)
Viktor Reshniak, Clayton G. Webster
Robust Learning with Implicit Residual Networks. Mach. Learn. Knowl. Extr. 3 (1) (2021)
Anton Dereventsov, Ranga Raju Vatsavai, Clayton G. Webster
On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks. ICDM (Workshops) (2021)
Viktor Reshniak, Jeremy Trageser, Clayton G. Webster
A Nonlocal Feature-Driven Exemplar-Based Approach for Image Inpainting. SIAM J. Imaging Sci. 13 (4) (2020)
Yiming Xu, Akil Narayan, Hoang Tran, Clayton G. Webster
Analysis of The Ratio of $\ell_1$ and $\ell_2$ Norms in Compressed Sensing. CoRR (2020)
Armenak Petrosyan, Anton Dereventsov, Clayton G. Webster
Neural network integral representations with the ReLU activation function. MSML (2020)
Anton Dereventsov, Clayton G. Webster, Joseph D. Daws Jr.
An adaptive stochastic gradient-free approach for high-dimensional blackbox optimization. CoRR (2020)
Joseph Daws Jr., Armenak Petrosyan, Hoang Tran, Clayton G. Webster
-Minimization Approach For Wavelet Reconstruction of Signals and Images. CoRR (2019)
Anton Dereventsov, Armenak Petrosyan, Clayton G. Webster
Greedy Shallow Networks: A New Approach for Constructing and Training Neural Networks. CoRR (2019)
Viktor Reshniak, Clayton G. Webster
Robust learning with implicit residual networks. CoRR (2019)
Anton Dereventsov, Armenak Petrosyan, Clayton G. Webster
Neural network integral representations with the ReLU activation function. CoRR (2019)
Max D. Gunzburger, Michael Schneier, Clayton G. Webster, Guannan Zhang
An Improved Discrete Least-Squares/Reduced-Basis Method for Parameterized Elliptic PDEs. J. Sci. Comput. 81 (1) (2019)
Joseph Daws Jr., Clayton G. Webster
Analysis of Deep Neural Networks with Quasi-optimal polynomial approximation rates. CoRR (2019)
Viktor Reshniak, Jeremy Trageser, Clayton G. Webster
A nonlocal feature-driven exemplar-based approach for image inpainting. CoRR (2019)
Joseph Daws Jr., Clayton G. Webster
A Polynomial-Based Approach for Architectural Design and Learning with Deep Neural Networks. CoRR (2019)
Abdellah Chkifa, Nick C. Dexter, Hoang Tran, Clayton G. Webster
Polynomial approximation via compressed sensing of high-dimensional functions on lower sets. Math. Comput. 87 (311) (2018)
Armenak Petrosyan, Hoang Tran, Clayton G. Webster
Reconstruction of jointly sparse vectors via manifold optimization. CoRR (2018)
Hoang Tran, Clayton G. Webster, Guannan Zhang
Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients. Numerische Mathematik 137 (2) (2017)
Miroslav Stoyanov, Clayton G. Webster
A dynamically adaptive sparse grids method for quasi-optimal interpolation of multidimensional functions. Comput. Math. Appl. 71 (11) (2016)
Diego Galindo, Peter Jantsch, Clayton G. Webster, Guannan Zhang
Accelerating Stochastic Collocation Methods for Partial Differential Equations with Random Input Data. SIAM/ASA J. Uncertain. Quantification 4 (1) (2016)
Nick C. Dexter, Clayton G. Webster, Guannan Zhang
Explicit cost bounds of stochastic Galerkin approximations for parameterized PDEs with random coefficients. Comput. Math. Appl. 71 (11) (2016)
Vincent Heuveline, Michael Schick, Clayton G. Webster, Peter Zaspel
Uncertainty Quantification and High Performance Computing (Dagstuhl Seminar 16372). Dagstuhl Reports 6 (9) (2016)
Guannan Zhang, Weidong Zhao, Clayton G. Webster, Max D. Gunzburger
Numerical methods for a class of nonlocal diffusion problems with the use of backward SDEs. Comput. Math. Appl. 71 (11) (2016)
Guannan Zhang, Clayton G. Webster, Max D. Gunzburger, John V. Burkardt
Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection. SIAM Rev. 58 (3) (2016)
Aretha L. Teckentrup, Peter Jantsch, Clayton G. Webster, Max D. Gunzburger
A Multilevel Stochastic Collocation Method for Partial Differential Equations with Random Input Data. SIAM/ASA J. Uncertain. Quantification 3 (1) (2015)
Guannan Zhang, Clayton G. Webster, Max D. Gunzburger, John V. Burkardt
A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection. SIAM J. Numer. Anal. 53 (3) (2015)
Miroslav Stoyanov, Clayton G. Webster
Numerical Analysis of Fixed Point Algorithms in the Presence of Hardware Faults. SIAM J. Sci. Comput. 37 (5) (2015)
Rick Archibald, Clayton G. Webster
Foreword. Int. J. Comput. Math. 91 (4) (2014)
Feng Bao, Yanzhao Cao, Clayton G. Webster, Guannan Zhang
A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations. SIAM/ASA J. Uncertain. Quantification 2 (1) (2014)
Max D. Gunzburger, Clayton G. Webster, Guannan Zhang
Stochastic finite element methods for partial differential equations with random input data. Acta Numer. 23 (2014)
Clayton G. Webster, Guannan Zhang, Max D. Gunzburger
An adaptive sparse-grid iterative ensemble Kalman filter approach for parameter field estimation. Int. J. Comput. Math. 91 (4) (2014)
Fabio Nobile, Raúl Tempone, Clayton G. Webster
A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data. SIAM J. Numer. Anal. 46 (5) (2008)
Fabio Nobile, Raúl Tempone, Clayton G. Webster
An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data. SIAM J. Numer. Anal. 46 (5) (2008)