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The Any Light Particle Search II (ALPS II) is a light shining through a wall experiment probing the existence of axions and axion-like particles using a 1064 nm laser source. While ALPS II is already taking data using a heterodyne based…

After the discovery of a Higgs boson in 2012 at the CERN Large Hadron Collider (LHC) the detailed study of its properties, and most importantly its couplings to other particles, has started. This is a very important task to be completed, in…

High Energy Physics - Phenomenology · Physics 2016-03-08 Julien Baglio

We consider the problem of best subset selection (BSS) under high-dimensional sparse linear regression model. Recently, Guo et al. (2020) showed that the model selection performance of BSS depends on a certain identifiability margin, a…

Statistics Theory · Mathematics 2025-04-15 Saptarshi Roy , Ambuj Tewari , Ziwei Zhu

Classical learning theory suggests that the optimal generalization performance of a machine learning model should occur at an intermediate model complexity, with simpler models exhibiting high bias and more complex models exhibiting high…

Machine Learning · Statistics 2020-11-09 Ben Adlam , Jeffrey Pennington

Phase segregation, the process by which the components of a binary mixture spontaneously separate, is a key process in the evolution and design of many chemical, mechanical, and biological systems. In this work, we present a data-driven…

Machine Learning · Computer Science 2018-03-28 Amir Barati Farimani , Joseph Gomes , Rishi Sharma , Franklin L. Lee , Vijay S. Pande

Destructive interference between signal and background processes poses a fundamental challenge in searches for top-philic scalar resonances, significantly reducing experimental sensitivity to well-motivated extensions of the Higgs sector.…

High Energy Physics - Phenomenology · Physics 2026-04-29 Diego A. Baron Moreno , Christoph Englert , Yvonne Peters

Clustering of large-scale structure provides significant cosmological information through the power spectrum of density perturbations. Additional information can be gained from higher-order statistics like the bispectrum, especially to…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-09 Marcel Schmittfull , Tobias Baldauf , Uroš Seljak

It is well known that accurate probabilistic predictors can be trained through empirical risk minimisation with proper scoring rules as loss functions. While such learners capture so-called aleatoric uncertainty of predictions, various…

Machine Learning · Computer Science 2023-01-31 Viktor Bengs , Eyke Hüllermeier , Willem Waegeman

In this talk we present a calculation of the dacay rate difference in the neutral $B_s-\bar{B}_s$ system, $\Delta \Gamma_{B_s}$, in next-to-leading order (NLO) QCD. We find a sizeable decrease compared to leading-order (LO) estimates: $…

High Energy Physics - Phenomenology · Physics 2007-05-23 Alexander Lenz

Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. To establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark…

High Energy Physics - Phenomenology · Physics 2018-09-06 Patrick T. Komiske , Eric M. Metodiev , Matthew D. Schwartz

We conduct an in depth study on the performance of deep learning based radio signal classification for radio communications signals. We consider a rigorous baseline method using higher order moments and strong boosted gradient tree…

Machine Learning · Computer Science 2018-03-14 Timothy J. O'Shea , Tamoghna Roy , T. Charles Clancy

Performing optimal Bayesian design for discriminating between competing models is computationally intensive as it involves estimating posterior model probabilities for thousands of simulated datasets. This issue is compounded further when…

Methodology · Statistics 2022-04-07 Markus Hainy , David J. Price , Olivier Restif , Christopher Drovandi

We consider the problem of making a quick decision in favor of one of two possible physical signal models while the numerical measurements are acquired by sensing devices featuring minimal digitization complexity. Therefore, the digital…

Signal Processing · Electrical Eng. & Systems 2019-10-29 Manuel S. Stein , Michael Fauß

The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more or less the different explanatory factors of variation behind…

Machine Learning · Computer Science 2014-04-24 Yoshua Bengio , Aaron Courville , Pascal Vincent

In online classification, a learner is presented with a sequence of examples and aims to predict their labels in an online fashion so as to minimize the total number of mistakes. In the self-directed variant, the learner knows in advance…

Machine Learning · Computer Science 2023-08-08 Ilias Diakonikolas , Vasilis Kontonis , Christos Tzamos , Nikos Zarifis

Finding discriminant functions of minimum risk binary classification systems is a novel geometric locus problem -- which requires solving a system of fundamental locus equations of binary classification -- subject to deep-seated statistical…

Machine Learning · Computer Science 2023-01-03 Denise M. Reeves

The identification of the intermediate-mass Higgs process $\gamma\gamma\to H \to b \bar b$ will be one of the most important goals of a future photon linear collider. Potentially important backgrounds from the continuum $\gamma\gamma \to c…

High Energy Physics - Phenomenology · Physics 2011-01-25 D. L. Borden , V. A. Khoze , W. J. Stirling , J. Ohnemus

Autonomous driving is a challenging scenario for image segmentation due to the presence of uncontrolled environmental conditions and the eventually catastrophic consequences of failures. Previous work suggested that a biologically motivated…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Pablo Hernández-Cámara , Jorge Vila-Tomás , Paula Dauden-Oliver , Nuria Alabau-Bosque , Valero Laparra , Jesús Malo

After a brief introduction to Deep Inelastic Scattering in the Bjorken limit and in the Regge Limit we discuss the operator product expansion in terms of non local string operator and in terms of Wilson lines. We will show how the…

High Energy Physics - Phenomenology · Physics 2010-02-25 Giovanni Antonio Chirilli

We present a general method of associating next-to-leading order weights to leading order phase space configurations at hadron colliders. The method relies on a re-organization of phase space for the real radiation contributions, defining a…

High Energy Physics - Phenomenology · Physics 2013-11-25 John M. Campbell , Walter T. Giele , Ciaran Williams