Daniel Sanz-Alonso

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 38

Top Topics

Monte Carlo Methods

Variational Inference

Acceptance Rate

Inverse Problems

Top Venues

SIAM/ASA J. Uncertain. Quantification

J. Mach. Learn. Res.

SIAM J. Math. Data Sci.

Publications

Daniel Sanz-Alonso, Omar Al Ghattas
A First Course in Monte Carlo Methods. CoRR (2024)
Daniel Sanz-Alonso, Nathan Waniorek
Hierarchical Bayesian Inverse Problems: A High-Dimensional Statistics Viewpoint. CoRR (2024)
Hwanwoo Kim, Daniel Sanz-Alonso, Ruiyi Yang
Optimization on Manifolds via Graph Gaussian Processes. SIAM J. Math. Data Sci. 6 (1) (2024)
Omar Al Ghattas, Jiajun Bao, Daniel Sanz-Alonso
Ensemble Kalman Filters with Resampling. SIAM/ASA J. Uncertain. Quantification 12 (2) (2024)
Melissa Adrian, Daniel Sanz-Alonso, Rebecca Willett
Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet. CoRR (2024)
Daniel Sanz-Alonso, Nathan Waniorek
Analysis of a Computational Framework for Bayesian Inverse Problems: Ensemble Kalman Updates and MAP Estimators under Mesh Refinement. SIAM/ASA J. Uncertain. Quantification 12 (1) (2024)
Hwanwoo Kim, Daniel Sanz-Alonso
Bayesian Optimization with Noise-Free Observations: Improved Regret Bounds via Random Exploration. CoRR (2024)
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett
Reduced-Order Autodifferentiable Ensemble Kalman Filters. CoRR (2023)
Daniel Sanz-Alonso, Nathan Waniorek
Analysis of a Computational Framework for Bayesian Inverse Problems: Ensemble Kalman Updates and MAP Estimators Under Mesh Refinement. CoRR (2023)
Daniel Sanz-Alonso, Ruiyi Yang
Gaussian Process Regression under Computational and Epistemic Misspecification. CoRR (2023)
Omar Al Ghattas, Jiajun Bao, Daniel Sanz-Alonso
Ensemble Kalman Filters with Resampling. CoRR (2023)
Shiv Agrawal, Hwanwoo Kim, Daniel Sanz-Alonso, Alexander Strang
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors. SIAM/ASA J. Uncertain. Quantification 10 (4) (2022)
Nicolás García Trillos, Daniel Sanz-Alonso, Ruiyi Yang
Mathematical Foundations of Graph-Based Bayesian Semi-Supervised Learning. CoRR (2022)
Daniel Sanz-Alonso, Ruiyi Yang
Unlabeled Data Help in Graph-Based Semi-Supervised Learning: A Bayesian Nonparametrics Perspective. J. Mach. Learn. Res. 23 (2022)
Hwanwoo Kim, Daniel Sanz-Alonso, Ruiyi Yang
Optimization on Manifolds via Graph Gaussian Processes. CoRR (2022)
Daniel Sanz-Alonso, Ruiyi Yang
Finite Element Representations of Gaussian Processes: Balancing Numerical and Statistical Accuracy. SIAM/ASA J. Uncertain. Quantification 10 (4) (2022)
Hwanwoo Kim, Daniel Sanz-Alonso, Alexander Strang
Hierarchical Ensemble Kalman Methods with Sparsity-Promoting Generalized Gamma Hyperpriors. CoRR (2022)
Omar Al Ghattas, Daniel Sanz-Alonso
Non-Asymptotic Analysis of Ensemble Kalman Updates: Effective Dimension and Localization. CoRR (2022)
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett
Autodifferentiable Ensemble Kalman Filters. SIAM J. Math. Data Sci. 4 (2) (2022)
John Harlim, Shixiao W. Jiang, Hwanwoo Kim, Daniel Sanz-Alonso
Graph-based Prior and Forward Models for Inverse Problems on Manifolds with Boundaries. CoRR (2021)
Daniel Sanz-Alonso, Zijian Wang
Bayesian Update with Importance Sampling: Required Sample Size. Entropy 23 (1) (2021)
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett
Auto-differentiable Ensemble Kalman Filters. CoRR (2021)
Daniel Sanz-Alonso, Ruiyi Yang
Finite Element Representations of Gaussian Processes: Balancing Numerical and Statistical Accuracy. CoRR (2021)
Mari Paz Calvo, Daniel Sanz-Alonso, Jesús María Sanz-Serna
HMC: Reducing the number of rejections by not using leapfrog and some results on the acceptance rate. J. Comput. Phys. 437 (2021)
Neil K. Chada, Yuming Chen, Daniel Sanz-Alonso
Iterative Ensemble Kalman Methods: A Unified Perspective with Some New Variants. CoRR (2020)
Nicolás García Trillos, Zachary Kaplan, Thabo Samakhoana, Daniel Sanz-Alonso
On the consistency of graph-based Bayesian semi-supervised learning and the scalability of sampling algorithms. J. Mach. Learn. Res. 21 (2020)
Daniel Sanz-Alonso, Ruiyi Yang
The SPDE Approach to Matérn Fields: Graph Representations. CoRR (2020)
John Harlim, Daniel Sanz-Alonso, Ruiyi Yang
Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds. SIAM/ASA J. Uncertain. Quantification 8 (4) (2020)
Daniele Bigoni, Yuming Chen, Nicolás García Trillos, Youssef M. Marzouk, Daniel Sanz-Alonso
Data-Driven Forward Discretizations for Bayesian Inversion. CoRR (2020)
Nicolás García Trillos, Zachary Kaplan, Daniel Sanz-Alonso
Variational Characterizations of Local Entropy and Heat Regularization in Deep Learning. CoRR (2019)
Nicolás García Trillos, Daniel Sanz-Alonso, Ruiyi Yang
Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis. J. Mach. Learn. Res. 20 (2019)
John Harlim, Daniel Sanz-Alonso, Ruiyi Yang
Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds. CoRR (2019)
Mari Paz Calvo, Daniel Sanz-Alonso, Jesús María Sanz-Serna
HMC: avoiding rejections by not using leapfrog and some results on the acceptance rate. CoRR (2019)
Nicolás García Trillos, Daniel Sanz-Alonso, Ruiyi Yang
Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis. CoRR (2019)
Nicolás García Trillos, Zachary Kaplan, Daniel Sanz-Alonso
Variational Characterizations of Local Entropy and Heat Regularization in Deep Learning. Entropy 21 (5) (2019)
Nicolás García Trillos, Daniel Sanz-Alonso
Continuum Limits of Posteriors in Graph Bayesian Inverse Problems. SIAM J. Math. Anal. 50 (4) (2018)
Daniel Sanz-Alonso
Importance Sampling and Necessary Sample Size: An Information Theory Approach. SIAM/ASA J. Uncertain. Quantification 6 (2) (2018)
Nicolás García Trillos, Zachary Kaplan, Thabo Samakhoana, Daniel Sanz-Alonso
On the Consistency of Graph-based Bayesian Learning and the Scalability of Sampling Algorithms. CoRR (2017)
Daniel Sanz-Alonso, Andrew M. Stuart
Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems. SIAM/ASA J. Uncertain. Quantification 3 (1) (2015)