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Previous works on depression detection use datasets collected in similar environments to train and test the models. In practice, however, the train and test distributions cannot be guaranteed to be identical. Distribution shifts can be…

Machine Learning · Computer Science 2024-04-09 Sri Harsha Dumpala , Chandramouli Shama Sastry , Rudolf Uher , Sageev Oore

A description of the current state of the project for the study of coherent elastic neutrino-atom scattering using a tritium source and liquid helium detector is given. The project was proposed in our paper in 2019 and its main goal is to…

Many algorithms in computer vision and robotics make strong assumptions about uncertainty, and rely on the validity of these assumptions to produce accurate and consistent state estimates. In practice, dynamic environments may degrade…

Robotics · Computer Science 2017-08-04 Valentin Peretroukhin , William Vega-Brown , Nicholas Roy , Jonathan Kelly

The upcoming Karlsruhe Tritium Neutrino (KATRIN) experiment will put unprecedented constraints on the absolute mass of the electron neutrino, $\mnue$. In this paper we investigate how this information on $\mnue$ will affect our constraints…

Astrophysics · Physics 2010-12-09 Jostein R. Kristiansen , Oystein Elgaroy

We explore beta decays in a dark background field, which could be formed by dark matter, dark energy or a fifth force potential. In such scenarios, the neutrino's dispersion relation will be modified by its collective interaction with the…

High Energy Physics - Phenomenology · Physics 2023-07-25 Guo-yuan Huang , Werner Rodejohann

Rolling origin forecast instability refers to variability in forecasts for a specific period induced by updating the forecast when new data points become available. Recently, an extension to the N-BEATS model for univariate time series…

Machine Learning · Computer Science 2025-01-22 Daan Caljon , Jeff Vercauteren , Simon De Vos , Wouter Verbeke , Jente Van Belle

We present a framework for learning of modeling uncertainties in Linear Time Invariant (LTI) systems. We propose a methodology to extend the dynamics of an LTI (without uncertainty) with an uncertainty model, based on measured data, to…

Systems and Control · Electrical Eng. & Systems 2023-11-01 Farhad Ghanipoor , Carlos Murguia , Peyman Mohajerin Esfahani , Nathan van de Wouw

Time-Series (TS) exhibits pronounced non-stationarity. Consequently, most forecasting methods display compromised robustness to concept drift, despite the prevalent application of instance normalization. We tackle this challenge by first…

Machine Learning · Computer Science 2026-01-29 Daojun Liang , Jing Chen , Xiao Wang , Yinglong Wang , Shuo Li

The mono-energetic conversion electrons from the decay of 83mKr represent a unique tool for the energy calibration, energy scale monitoring and systematic studies of the tritium beta spectrum measurement in the neutrino mass experiment…

Instrumentation and Detectors · Physics 2009-02-03 D. Venos , J. Kaspar , M. Zboril , O. Dragoun , J. Bonn , A. Kovalik , O. Lebeda , M. Rysavy , K. Schlosser , A. Spalek , Ch. Weinheimer

The KATRIN experiment will probe the neutrino mass by measuring the beta-electron energy spectrum near the endpoint of tritium beta-decay. An integral energy analysis will be performed by an electro-static spectrometer (Main Spectrometer),…

Instrumentation and Detectors · Physics 2016-05-04 M. Arenz , M. Babutzka , M. Bahr , J. P. Barrett , S. Bauer , M. Beck , A. Beglarian , J. Behrens , T. Bergmann , U. Besserer , J. Blümer , L. I. Bodine , K. Bokeloh , J. Bonn , B. Bornschein , L. Bornschein , S. Büsch , T. H. Burritt , S. Chilingaryan , T. J. Corona , L. De Viveiros , P. J. Doe , O. Dragoun , G. Drexlin , S. Dyba , S. Ebenhöch , K. Eitel , E. Ellinger , S. Enomoto , M. Erhard , D. Eversheim , M. Fedkevych , A. Felden , S. Fischer , J. A. Formaggio , F. Fränkle , D. Furse , M. Ghilea , W. Gil , F. Glück , A. Gonzalez Urena , S. Görhardt , S. Groh , S. Grohmann , R. Grössle , R. Gumbsheimer , M. Hackenjos , V. Hannen , F. Harms , N. Hauÿmann , F. Heizmann , K. Helbing , W. Herz , S. Hickford , D. Hilk , B. Hillen , T. Höhn , B. Holzapfel , M. Hötzel , M. A. Howe , A. Huber , A. Jansen , N. Kernert , L. Kippenbrock , M. Kleesiek , M. Klein , A. Kopmann , A. Kosmider , A. Kovalík , B. Krasch , M. Kraus , H. Krause , M. Krause , L. Kuckert , B. Kuffner , L. La Cascio , O. Lebeda , B. Leiber , J. Letnev , V. M. Lobashev , A. Lokhov , E. Malcherek , M. Mark , E. L. Martin , S. Mertens , S. Mirz , B. Monreal , K. Müller , M. Neuberger , H. Neumann , S. Niemes , M. Noe , N. S. Oblath , A. Off , H. -W. Ortjohann , A. Osipowicz , E. Otten , D. S. Parno , P. Plischke , A. W. P. Poon , M. Prall , F. Priester , P. C. -O. Ranitzsch , J. Reich , O. Rest , R. G. H. Robertson , M. Röllig , S. Rosendahl , S. Rupp , M. Rysavy , K. Schlösser , M. Schlösser , K. Schönung , M. Schrank , J. Schwarz , W. Seiler , H. Seitz-Moskaliuk , J. Sentkerestiova , A. Skasyrskaya , M. Slezak , A. Spalek , M. Steidl , N. Steinbrink , M. Sturm , M. Suesser , H. H. Telle , T. Thümmler , N. Titov , I. Tkachev , N. Trost , A. Unru , K. Valerius , D. Venos , R. Vianden , S. Vöcking , B. L. Wall , N. Wandkowsky , M. Weber , C. Weinheimer , C. Weiss , S. Welte , J. Wendel , K. L. Wierman , J. F. Wilkerson , D. Winzen , J. Wolf , S. Wüstling , M. Zacher , S. Zadoroghny , M. Zboril

Learning stable dynamics from observed time-series data is an essential problem in robotics, physical modeling, and systems biology. Many of these dynamics are represented as an inputs-output system to communicate with the external…

Dynamical Systems · Mathematics 2023-01-18 Yuji Okamoto , Ryosuke Kojima

Right-handed neutrinos are a natural extension of the Standard Model of particle physics. Such particles would only interact through the mixing with the left-handed neutrinos, hence they are called sterile neutrinos. If their mass were in…

Instrumentation and Detectors · Physics 2020-03-12 Manuel Lebert , Tim Brunst , Thibaut Houdy , Susanne Mertens , Daniel Siegmann

Spatio-temporal forecasting is crucial in many domains, such as transportation, meteorology, and energy. However, real-world scenarios frequently present challenges such as signal anomalies, noise, and distributional shifts. Existing…

Machine Learning · Computer Science 2025-10-30 Wei Chen , Yuxuan Liang

We present a critical survey on the consistency of uncertainty quantification used in deep learning and highlight partial uncertainty coverage and many inconsistencies. We then provide a comprehensive and statistically consistent framework…

Machine Learning · Computer Science 2026-01-14 Peter Jan van Leeuwen , J. Christine Chiu , C. Kevin Yang

In this paper, we present an algorithm for learning time-correlated measurement covariances for application in batch state estimation. We parameterize the inverse measurement covariance matrix to be block-banded, which conveniently…

Robotics · Computer Science 2023-03-14 David J. Yoon , Timothy D. Barfoot

We study the discovery potential of future beta decay experiments on searches for the neutrino mass in the sub-eV range, and, in particular, KATRIN experiment with sensitivity $m > 0.3$ eV. Effects of neutrino mass and mixing on the beta…

High Energy Physics - Phenomenology · Physics 2014-11-17 Y. Farzan , O. L. G. Peres , A. Yu. Smirnov

Accurately forecasting carbon prices is essential for informed energy market decision-making, guiding sustainable energy planning, and supporting effective decarbonization strategies. However, it remains challenging due to structural breaks…

Machine Learning · Computer Science 2025-11-21 Runsheng Ren , Jing Li , Yanxiu Li , Shixun Huang , Jun Shen , Wanqing Li , John Le , Sheng Wang

The KATRIN experiment in Karlsruhe Germany will monitor the decay of tritium, which produces an electron-antineutrino. While the present upper bound for its mass is 2 eV/$c^2$, KATRIN will search down to 0.2 eV$/c^2$. If the dark matter of…

Cosmology and Nongalactic Astrophysics · Physics 2011-04-01 Theo M. Nieuwenhuizen , Andrea Morandi

Early warning indicators often suffer from the shortness and coarse-graining of real-world time series. Furthermore, the typically strong and correlated noise contributions in real applications are severe drawbacks for statistical measures.…

Data Analysis, Statistics and Probability · Physics 2026-03-03 Martin Heßler , Oliver Kamps

We study the physics potential of future long-baseline neutrino oscillation experiments at large $\theta_{13}$, focusing especially on systematic uncertainties. We discuss superbeams, \bbeams, and neutrino factories, and for the first time…

High Energy Physics - Phenomenology · Physics 2013-03-14 Pilar Coloma , Patrick Huber , Joachim Kopp , Walter Winter
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