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Opacity is an important information-flow security property in the analysis of cyber-physical systems. It captures the plausible deniability of the system's secret behavior in the presence of an intruder that may access the information flow.…

Systems and Control · Computer Science 2019-02-26 Xiang Yin , Majid Zamani

Outliers are ubiquitous in modern data sets. Distance-based techniques are a popular non-parametric approach to outlier detection as they require no prior assumptions on the data generating distribution and are simple to implement. Scaling…

Machine Learning · Statistics 2016-05-04 Mario Lucic , Olivier Bachem , Andreas Krause

We study the problem of testing identity against a given distribution with a focus on the high confidence regime. More precisely, given samples from an unknown distribution $p$ over $n$ elements, an explicitly given distribution $q$, and…

Data Structures and Algorithms · Computer Science 2019-01-17 Ilias Diakonikolas , Themis Gouleakis , John Peebles , Eric Price

Light scattering is one of the most established wave phenomena in optics, lying at the heart of light-matter interactions and of crucial importance for nanophotonic applications. Passivity, causality and energy conservation imply strict…

Optics · Physics 2022-11-23 Seunghwi Kim , Sergey Lepeshov , Alex Krasnok , Andrea Alù

Causal inference from observational data provides strong evidence for the best action in decision-making without performing expensive randomized trials. The effect of an action is usually not identifiable under unobserved confounding, even…

Machine Learning · Computer Science 2026-02-02 Md Musfiqur Rahman , Ziwei Jiang , Hilaf Hasson , Murat Kocaoglu

The vast majority of uncertainty quantification methods for deep object detectors such as variational inference are based on the network output. Here, we study gradient-based epistemic uncertainty metrics for deep object detectors to obtain…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Tobias Riedlinger , Matthias Rottmann , Marius Schubert , Hanno Gottschalk

Classifiers are often tested on relatively small data sets, which should lead to uncertain performance metrics. Nevertheless, these metrics are usually taken at face value. We present an approach to quantify the uncertainty of…

Machine Learning · Statistics 2021-03-05 Niklas Tötsch , Daniel Hoffmann

Identification of input data points relevant for the classifier (i.e. serve as the support vector) has recently spurred the interest of researchers for both interpretability as well as dataset debugging. This paper presents an in-depth…

Machine Learning · Computer Science 2020-09-30 Dominique Mercier , Shoaib Ahmed Siddiqui , Andreas Dengel , Sheraz Ahmed

Complex systems are found in most branches of science. It is still argued how to best quantify their complexity and to what end. One prominent measure of complexity (the statistical complexity) has an operational meaning in terms of the…

Data Analysis, Statistics and Probability · Physics 2011-10-24 Karoline Wiesner , Mile Gu , Elisabeth Rieper , Vlatko Vedral

We describe the generation of single-band point source catalogues from submillimetre Herschel-SPIRE observations taken as part of the Science Demonstration Phase of the Herschel Multi-tiered Extragalactic Survey (HerMES). Flux densities are…

We prove a strong concentration result about the natural collision estimator, which counts the number of collisions that occur within an iid sample. This estimator is at the heart of algorithms used for uniformity testing and entropy…

Information Theory · Computer Science 2020-06-26 Maciej Skorski

Transient detection and flux measurement via image subtraction stand at the base of time domain astronomy. Due to the varying seeing conditions, the image subtraction process is non-trivial, and existing solutions suffer from a variety of…

Instrumentation and Methods for Astrophysics · Physics 2016-10-12 Barak Zackay , Eran O. Ofek , Avishay Gal-Yam

In physical-layer security, one of the most fundamental issues is the secrecy capacity. The objective of this paper is to determine the secrecy capacity for an indoor visible light communication system consisting of a transmitter, a…

Information Theory · Computer Science 2021-09-24 Jin-Yuan Wang , Xian-Tao Fu , Jun-Bo Wang , Min Lin , Julian Cheng , Mohamed-Slim Alouini

Out-of-Distribution detection between dataset pairs has been extensively explored with generative models. We show that likelihood-based Out-of-Distribution detection can be extended to diffusion models by leveraging the fact that they, like…

Machine Learning · Computer Science 2023-10-27 Joseph Goodier , Neill D. F. Campbell

In this paper we present a model independent analysis method following Bayesian statistics to analyse data from a generic counting experiment and apply it to the search for neutrinos from point sources. We discuss a test statistic defined…

High Energy Astrophysical Phenomena · Physics 2015-06-12 D. Bose , L. Brayeur , M. Casier , K. D. de Vries , G. Golup , N. van Eijndhoven

We review the effects of source size in interferometric observations and focus on the cases of very compact sources. If a source is extremely compact and/or weak (so it is not possible to detect signature of source structure in the…

Instrumentation and Methods for Astrophysics · Physics 2015-06-04 I. Marti-Vidal , M. A. Perez-Torres , A. P. Lobanov

The next generation of telescopes will acquire terabytes of image data on a nightly basis. Collectively, these large images will contain billions of interesting objects, which astronomers call sources. The astronomers' task is to construct…

Applications · Statistics 2009-10-29 David A. Friedenberg , Christopher R. Genovese

Statistical inference of population parameters of astrophysical sources is challenging. It requires accounting for selection effects, which stem from the artificial separation between bright detected and dim undetected sources that is…

Instrumentation and Methods for Astrophysics · Physics 2022-11-10 Noemi Anau Montel , Christoph Weniger

A central problem in Binary Hypothesis Testing (BHT) is to determine the optimal tradeoff between the Type I error (referred to as false alarm) and Type II (referred to as miss) error. In this context, the exponential rate of convergence of…

Information Theory · Computer Science 2021-11-29 Sebastian Espinosa , Jorge F. Silva , Pablo Piantanida

Our present understanding of the extragalactic source counts and background radiation at infrared and sub-mm wavelengths is reviewed. Available count data are used to constrain evolutionary models of galaxies and Active Nuclei. The CIRB, on…

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