Designing an Optimal Sensor Network via Minimizing Information Loss
Fuente:
arXiv
Saved in:
| Main Authors: | Waxman, Daniel, Llorente, Fernando, Lamer, Katia, Djurić, Petar M. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Design-based causal inference in bipartite experiments
by: Lu, Sizhu, et al.
Published: (2025)
by: Lu, Sizhu, et al.
Published: (2025)
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo
by: Zhong, Shijie, et al.
Published: (2024)
by: Zhong, Shijie, et al.
Published: (2024)
Berry-Esseen bounds for design-based causal inference with possibly diverging treatment levels and varying group sizes
by: Shi, Lei, et al.
Published: (2022)
by: Shi, Lei, et al.
Published: (2022)
Asymptotic theory of the quadratic assignment procedure for dyadic data analysis
by: Shi, Lei, et al.
Published: (2024)
by: Shi, Lei, et al.
Published: (2024)
Forward selection and post-selection inference in factorial designs
by: Shi, Lei, et al.
Published: (2023)
by: Shi, Lei, et al.
Published: (2023)
Locally Optimal Design for A/B Testing in the Presence of Covariates and Network Connection
by: Zhang, Qiong, et al.
Published: (2020)
by: Zhang, Qiong, et al.
Published: (2020)
A Gaussian process and linear-based framework for computing cut distributions in modular Bayesian calibration of two chained computer models
by: Baldé, Oumar, et al.
Published: (2023)
by: Baldé, Oumar, et al.
Published: (2023)
ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization
by: Hui-Mean, Foo, et al.
Published: (2026)
by: Hui-Mean, Foo, et al.
Published: (2026)
Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning
by: Shen, Wanggang, et al.
Published: (2021)
by: Shen, Wanggang, et al.
Published: (2021)
mfEGRA: Multifidelity Efficient Global Reliability Analysis through Active Learning for Failure Boundary Location
by: Chaudhuri, Anirban, et al.
Published: (2019)
by: Chaudhuri, Anirban, et al.
Published: (2019)
"Sound and Fury": Nonlinear Functionals of Volatility Matrix in the Presence of Jump and Noise
by: Chen, Richard Y.
Published: (2024)
by: Chen, Richard Y.
Published: (2024)
Variational Sequential Optimal Experimental Design using Reinforcement Learning
by: Shen, Wanggang, et al.
Published: (2023)
by: Shen, Wanggang, et al.
Published: (2023)
Distributional Shrinkage I: Universal Denoiser Beyond Tweedie's Formula
by: Liang, Tengyuan
Published: (2025)
by: Liang, Tengyuan
Published: (2025)
Local regression on path spaces with signature metrics
by: Bayer, Christian, et al.
Published: (2025)
by: Bayer, Christian, et al.
Published: (2025)
Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes
by: Waxman, Daniel, et al.
Published: (2025)
by: Waxman, Daniel, et al.
Published: (2025)
Optimal Design in Repeated Testing for Count Data
by: Parsamaram, Parisa, et al.
Published: (2024)
by: Parsamaram, Parisa, et al.
Published: (2024)
Measuring and testing tail equivalence
by: Koike, Takaaki, et al.
Published: (2024)
by: Koike, Takaaki, et al.
Published: (2024)
Inequalities and bounds for expected order statistics from transform-ordered families
by: Arab, Tommaso Lando Idir, et al.
Published: (2024)
by: Arab, Tommaso Lando Idir, et al.
Published: (2024)
Likelihood Ratio Tests by Kernel Gaussian Embedding
by: Santoro, Leonardo V., et al.
Published: (2025)
by: Santoro, Leonardo V., et al.
Published: (2025)
Predictive Inference via Kernel Density Estimates
by: Hilbert, Torey
Published: (2026)
by: Hilbert, Torey
Published: (2026)
Mean--Variance Risk-Aware Bayesian Optimal Experimental Design for Nonlinear Models
by: Shen, Wanggang, et al.
Published: (2026)
by: Shen, Wanggang, et al.
Published: (2026)
Bayesian Mixtures Models with Repulsive and Attractive Atoms
by: Beraha, Mario, et al.
Published: (2023)
by: Beraha, Mario, et al.
Published: (2023)
Variational Bayesian Optimal Experimental Design with Normalizing Flows
by: Dong, Jiayuan, et al.
Published: (2024)
by: Dong, Jiayuan, et al.
Published: (2024)
Bump hunting through density curvature features
by: Chacón, José E., et al.
Published: (2022)
by: Chacón, José E., et al.
Published: (2022)
A Bayesian Updating Framework for Long-term Multi-Environment Trial Data in Plant Breeding
by: Bark, Stephan, et al.
Published: (2026)
by: Bark, Stephan, et al.
Published: (2026)
The multivariate fractional Ornstein-Uhlenbeck process
by: Dugo, Ranieri, et al.
Published: (2024)
by: Dugo, Ranieri, et al.
Published: (2024)
Gaussian Approximation for the Moving Averaged Modulus Wavelet Transform and its Variants
by: Liu, Gi-Ren, et al.
Published: (2023)
by: Liu, Gi-Ren, et al.
Published: (2023)
Convergence Rate Analysis in Limit Theorems for Nonlinear Functionals of the Second Wiener Chaos
by: Liu, Gi-Ren
Published: (2023)
by: Liu, Gi-Ren
Published: (2023)
Learning from Neighbors with PHIBP: Predicting Infectious Disease Dynamics in Data-Sparse Environments
by: Fong, Edwin, et al.
Published: (2025)
by: Fong, Edwin, et al.
Published: (2025)
Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products
by: Yuan, Gan, et al.
Published: (2023)
by: Yuan, Gan, et al.
Published: (2023)
Bayesian nonparametric inference on a Fréchet class
by: Dreassi, Emanuela, et al.
Published: (2025)
by: Dreassi, Emanuela, et al.
Published: (2025)
Least squares estimation of the transition density in bifurcating Markov models
by: Penda, S. Valère Bitseki
Published: (2025)
by: Penda, S. Valère Bitseki
Published: (2025)
Inverting Poisson-Laguerre tessellations
by: van der Jagt, Thomas, et al.
Published: (2026)
by: van der Jagt, Thomas, et al.
Published: (2026)
High-dimensional variable clustering based on maxima of a weakly dependent random process
by: Boulin, Alexis, et al.
Published: (2023)
by: Boulin, Alexis, et al.
Published: (2023)
Sharp Convergence Rates of Empirical Unbalanced Optimal Transport for Spatio-Temporal Point Processes
by: Struleva, Marina, et al.
Published: (2025)
by: Struleva, Marina, et al.
Published: (2025)
Computationally efficient multi-level Gaussian process regression for functional data observed under completely or partially regular sampling designs
by: Hoffmann, Adam Gorm, et al.
Published: (2024)
by: Hoffmann, Adam Gorm, et al.
Published: (2024)
Gradient-based Active Learning with Gaussian Processes for Global Sensitivity Analysis
by: Lambert, Guerlain, et al.
Published: (2026)
by: Lambert, Guerlain, et al.
Published: (2026)
Convolutional neural networks for valid and efficient causal inference
by: Ghasempour, Mohammad, et al.
Published: (2023)
by: Ghasempour, Mohammad, et al.
Published: (2023)
Design-Based Inference under Random Potential Outcomes
by: Yang, Yukai
Published: (2025)
by: Yang, Yukai
Published: (2025)
Nonparametric Estimation via Expected Order Statistics
by: Lando, Tommaso, et al.
Published: (2026)
by: Lando, Tommaso, et al.
Published: (2026)
Similar Items
-
Design-based causal inference in bipartite experiments
by: Lu, Sizhu, et al.
Published: (2025) -
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo
by: Zhong, Shijie, et al.
Published: (2024) -
Berry-Esseen bounds for design-based causal inference with possibly diverging treatment levels and varying group sizes
by: Shi, Lei, et al.
Published: (2022) -
Asymptotic theory of the quadratic assignment procedure for dyadic data analysis
by: Shi, Lei, et al.
Published: (2024) -
Forward selection and post-selection inference in factorial designs
by: Shi, Lei, et al.
Published: (2023)