Cover Image

Accurate, scalable, and efficient Bayesian optimal experimental design with derivative-informed neural operators

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Go, Jinwoo, Chen, Peng
Format:	Preprint
Published:	2023
Subjects:	Computational Engineering, Finance, and Science Optimization and Control Methodology 62K05, 35Q62, 62F15, 35R30, 35Q93, 65C60, 90C27 G.1.8; I.5.2; I.6.4
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Probabilistic Approach to Trajectory-Based Optimal Experimental Design
by: Attia, Ahmed
Published: (2026)

Probabilistic Approach to Black-Box Binary Optimization with Budget Constraints: Application to Sensor Placement
by: Attia, Ahmed
Published: (2024)

Empirical Decision Theory
by: Jansen, Christoph, et al.
Published: (2025)

Stein Variational Gradient Descent dynamics for highly concentrated kernels
by: Carrillo, José A., et al.
Published: (2026)

Radon--Wasserstein Gradient Flows for Interacting-Particle Sampling in High Dimensions
by: Hess-Childs, Elias, et al.
Published: (2026)

Uniform error bounds of the ensemble transform Kalman filter for infinite-dimensional dynamics with multiplicative covariance inflation
by: Takeda, Kota, et al.
Published: (2024)

A localized particle filter for geophysical data assimilation
by: Crisan, Dan, et al.
Published: (2025)

Physics-informed machine learning: A mathematical framework with applications to time series forecasting
by: Doumèche, Nathan
Published: (2025)

Asymptotic Consistency for Nonconvex Risk-Averse Stochastic Optimization with Infinite Dimensional Decision Spaces
by: Milz, Johannes, et al.
Published: (2022)

Nonlocal Approximation of Slow and Fast Diffusion
by: Craig, Katy, et al.
Published: (2023)

A Bayesian approach to inverse problems in spaces of measures
by: Huynh, Phuoc-Truong
Published: (2025)

The Stein-log-Sobolev inequality and the exponential rate of convergence for the continuous Stein variational gradient descent method
by: Carrillo, José A., et al.
Published: (2024)

Tverberg's theorem and multi-class support vector machines
by: Soberón, Pablo
Published: (2024)

Huber-based Robust System Identification with Near-Optimal Guarantees Across Independent and Adversarial Regimes
by: Kim, Jihun, et al.
Published: (2026)

On the Necessity of Two-Stage Estimation for Learning Dynamical Systems under Both Noise and Node-Wise Attacks
by: Kim, Jihun, et al.
Published: (2026)

Cover It Up! Bipartite Graphs Uncover Identifiability in Sparse Factor Analysis
by: Hosszejni, Darjus, et al.
Published: (2022)

Bayesian Covariance Uncertainty for Adaptive Pilot-Sampling Termination in Multi-fidelity Uncertainty Quantification
by: Coons, Thomas E., et al.
Published: (2025)

The Curious Problem of the Normal Inverse Mean: Robustness and Shrinkage
by: Ghosh, Soham, et al.
Published: (2024)

PDE-DKL: PDE-constrained deep kernel learning in high dimensionality
by: Yan, Weihao, et al.
Published: (2025)

Bayesian Conservative Policy Optimization (BCPO): A Novel Uncertainty-Calibrated Offline Reinforcement Learning with Credible Lower Bounds
by: Chatterjee, Debashis
Published: (2026)

Quantitative 2D propagation of smallness and control for 1D heat equations with power growth potentials
by: Wang, Yunlei
Published: (2024)

Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity
by: Wang, Shixiong, et al.
Published: (2023)

Distributional Robustness Bounds Generalization Errors
by: Wang, Shixiong, et al.
Published: (2022)

Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks
by: Høyheim, Eirik, et al.
Published: (2025)

Quantifying the Value of Seismic Structural Health Monitoring for post-earthquake recovery of electric power system in terms of resilience enhancement
by: Liang, Huangbin, et al.
Published: (2025)

Ultrahigh-Q chiral resonances empowered by multi-head attention deep learning
by: Zhang, Cong, et al.
Published: (2025)

Exotic traveling waves for a quasilinear Schrödinger equation with nonzero background
by: de Laire, André, et al.
Published: (2023)

FBMS: An R Package for Flexible Bayesian Model Selection and Model Averaging
by: Frommlet, Florian, et al.
Published: (2025)

Unified Robust Boosting
by: Wang, Zhu
Published: (2021)

Bayesian Generalized Nonlinear Models Offer Basis Free SINDy With Model Uncertainty
by: Hubin, Aliaksandr
Published: (2025)

Orbital stability of black solitons for quasilinear Schrödinger equations with nonzero conditions at infinity
by: Quiniou, Erwan Le
Published: (2026)

Wasserstein-Cramér-Rao Theory of Unbiased Estimation
by: Trillos, Nicolás García, et al.
Published: (2025)

Towards optimal sensor placement for inverse problems in spaces of measures
by: Huynh, Phuoc-Truong, et al.
Published: (2023)

Observability estimates for the Schrödinger equation on the equilateral triangle
by: Alphonse, Paul, et al.
Published: (2025)

Quantitative Local Convergence of Mean-Field Stein Variational Gradient Flow
by: Chizat, Lénaïc, et al.
Published: (2026)

Calibrated Counterfactual Conformal Fairness ($C^3F$): Post-hoc, Shift-Aware Coverage Parity via Conformal Prediction and Counterfactual Regularization
by: Alpay, Faruk, et al.
Published: (2025)

Micro-Macro Decomposition of Particle Swarm Optimization Methods
by: Herty, Michael, et al.
Published: (2025)

A Blob Method for Mean Field Control With Terminal Constraints
by: Craig, Katy, et al.
Published: (2024)

The Unified Non-Convex Framework for Robust Causal Inference: Overcoming the Gaussian Barrier and Optimization Fragility
by: Uehara, Eichi
Published: (2025)

Adaptive Transfer Clustering: A Unified Framework
by: Gu, Yuqi, et al.
Published: (2024)