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A variety of two-dimensional materials possess a band structure with an energy extremal ridge along a ring in momentum space. Examples are biased bilayer graphene, and surfaces and interfaces with a Rashba spin-orbit interaction where at…

Mesoscale and Nanoscale Physics · Physics 2017-01-02 Eugene B. Kolomeisky , Joseph P. Straley

Anomaly Detection is a relevant problem that arises in numerous real-world applications, especially when dealing with images. However, there has been little research for this task in the Continual Learning setting. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Davide Dalle Pezze , Eugenia Anello , Chiara Masiero , Gian Antonio Susto

An anomaly detection method based on deep autoencoders is proposed to address anomalies that often occur in enterprise-level ETL data streams. The study first analyzes multiple types of anomalies in ETL processes, including delays, missing…

Machine Learning · Computer Science 2025-11-04 Xin Chen , Saili Uday Gadgil , Kangning Gao , Yi Hu , Cong Nie

Due to the intractability of characterizing everything that looks unlike the normal data, anomaly detection (AD) is traditionally treated as an unsupervised problem utilizing only normal samples. However, it has recently been found that…

Computer Vision and Pattern Recognition · Computer Science 2023-01-29 Philipp Liznerski , Lukas Ruff , Robert A. Vandermeulen , Billy Joe Franks , Klaus-Robert Müller , Marius Kloft

Formulating learning systems for the detection of real-world anomalous events using only video-level labels is a challenging task mainly due to the presence of noisy labels as well as the rare occurrence of anomalous events in the training…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Muhammad Zaigham Zaheer , Arif Mahmood , Marcella Astrid , Seung-Ik Lee

Permeable porous coatings on a flat solid support significantly impact its electrostatic and electrokinetic properties. Existing work has focused on simplified cases, such as weakly charged and/or thick porous films, with limited…

Soft Condensed Matter · Physics 2020-12-02 Elena F. Silkina , Naren Bag , Olga I. Vinogradova

Anomaly detection refers to the task of finding unusual instances that stand out from the normal data. In several applications, these outliers or anomalous instances are of greater interest compared to the normal ones. Specifically in the…

Image and Video Processing · Electrical Eng. & Systems 2020-01-14 Manpreet Singh Minhas , John Zelek

Using CCD detectors onboard the forthcoming X-ray observatories Chandra and XMM, it is possible to devise a measurement of the absolute density of heavy elements in the hypothetical warm gas filling intercluster space. This gas may be the…

Astrophysics · Physics 2009-10-31 Maxim Markevitch

The force law within free suspended black films made of negatively charged Aerosol-OT (AOT) with added LiCl or CsCl is studied accurately using X-ray reflectivity (ca. 1{\AA}). We find an electrolyte concentration threshold above which a…

Soft Condensed Matter · Physics 2009-10-31 D. Sentenac , J. J. Benattar

Suppose the expectation $E(F(X))$ is to be estimated by the empirical averages of the values of $F$ on independent and identically distributed samples $\{X_i\}$. A sampling rule called the "screened" estimator is introduced, and its…

Probability · Mathematics 2009-09-29 Ioannis Kontoyiannis , Sean P. Meyn

Several scenarios beyond the Standard Model predict heavy long-lived particles as a result of a kinematic constraint, a conserved quantum number or a weak coupling. Such particles are possibly identified based on the detection through…

High Energy Physics - Experiment · Physics 2019-08-13 Shimpei Yamamoto

Current unsupervised anomaly localization approaches rely on generative models to learn the distribution of normal images, which is later used to identify potential anomalous regions derived from errors on the reconstructed images. However,…

Image and Video Processing · Electrical Eng. & Systems 2021-10-29 Julio Silva-Rodríguez , Valery Naranjo , Jose Dolz

We propose a supervised anomaly detection method based on neural density estimators, where the negative log likelihood is used for the anomaly score. Density estimators have been widely used for unsupervised anomaly detection. By the recent…

Machine Learning · Statistics 2019-04-15 Tomoharu Iwata , Yuki Yamanaka

Detecting anomalous faces has important applications. For example, a system might tell when a train driver is incapacitated by a medical event, and assist in adopting a safe recovery strategy. These applications are demanding, because they…

Computer Vision and Pattern Recognition · Computer Science 2018-02-19 Anand Bhattad , Jason Rock , David Forsyth

We consider an electrolyte solution confined by semipermeable membranes in contact with a salt-free solvent. Membranes are uncharged, but since small counter-ions leak-out into infinite salt-free reservoirs, we observe a distance-dependent…

Soft Condensed Matter · Physics 2014-08-19 Salim R. Maduar , Olga I. Vinogradova

MeV ultrafast electron diffraction (MUED) is a pump-probe technique used to study the dynamic structural evolution of materials. An ultrashort laser pulse triggers structural changes, which are then probed by an ultrashort relativistic…

Semi-supervised anomaly detection is based on the principle that potential anomalies are those records that look different from normal training data. However, in some cases we are specifically interested in anomalies that correspond to high…

Machine Learning · Computer Science 2025-06-06 Oliver Urs Lenz , Matthijs van Leeuwen

We report on the determination of electron densities, and their impact on the outflow masses and rates, measured in the central few hundred parsecs of 11 local luminous active galaxies. We show that the peak of the integrated line emission…

We investigate anomalous strong lens systems, particularly the effects of weak lensing by structures in the line of sight, in models with long-lived electrically charged massive particles (CHAMPs). In such models, matter density…

Cosmology and Nongalactic Astrophysics · Physics 2017-11-15 Ayuki Kamada , Kaiki Taro Inoue , Kazunori Kohri , Tomo Takahashi

Anomaly detection is being regarded as an unsupervised learning task as anomalies stem from adversarial or unlikely events with unknown distributions. However, the predictive performance of purely unsupervised anomaly detection often fails…

Machine Learning · Computer Science 2014-01-27 Nico Goernitz , Marius Micha Kloft , Konrad Rieck , Ulf Brefeld
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