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While deep learning has been very beneficial in data-rich settings, tasks with smaller training set often resort to pre-training or multitask learning to leverage data from other tasks. In this case, careful consideration is needed to…

Machine Learning · Computer Science 2021-08-26 Lucio M. Dery , Yann Dauphin , David Grangier

Overfitting & underfitting and stable training are an important challenges in machine learning. Current approaches for these issues are mixup, SamplePairing and BC learning. In our work, we state the hypothesis that mixing many images…

Machine Learning · Computer Science 2020-01-22 Maciej A. Czyzewski

The latest LHC data confirmed the existence of a Higgs-like particle and made interesting measurements on its decays into $\gamma \gamma$, $Z Z^\ast$, $W W^\ast$, $\tau^+ \tau^-$, and $b \bar{b}$. It is expected that a decay into $Z \gamma$…

High Energy Physics - Phenomenology · Physics 2015-06-22 Duarte Fontes , J. C. Romão , João P. Silva

The inclusive Higgs production rate through gluon fusion has been measured to be in agreement with the Standard Model (SM). We show that even if the inclusive Higgs production rate is very SM-like, a precise determination of the boosted…

High Energy Physics - Phenomenology · Physics 2015-06-19 Matthias Schlaffer , Michael Spannowsky , Michihisa Takeuchi , Andreas Weiler , Chris Wymant

The Higgs production and decay rates offer a new way to probe new physics beyond the Standard Model. While dynamics aiming at alleviating the hierarchy problem generically predict deviations in the Higgs rates, the current experimental…

High Energy Physics - Phenomenology · Physics 2015-06-18 Christophe Grojean , Ennio Salvioni , Matthias Schlaffer , Andreas Weiler

We propose a novel measure for template matching named Deformable Diversity Similarity -- based on the diversity of feature matches between a target image window and the template. We rely on both local appearance and geometric information…

Computer Vision and Pattern Recognition · Computer Science 2017-04-19 Itamar Talmi , Roey Mechrez , Lihi Zelnik-Manor

Supersymmetric models with extended electroweak gauge groups have the potential to enhance the Higgs quartic interaction through nondecoupling D-terms. We consider the D-term enhancement effect in a vector top partner model, where the…

High Energy Physics - Phenomenology · Physics 2014-06-10 Haiying Cai

Deep neural networks often make decisions based on the spurious correlations inherent in the dataset, failing to generalize in an unbiased data distribution. Although previous approaches pre-define the type of dataset bias to prevent the…

Computer Vision and Pattern Recognition · Computer Science 2021-08-24 Eungyeup Kim , Jihyeon Lee , Jaegul Choo

Attribution methods aim to explain a neural network's prediction by highlighting the most relevant image areas. A popular approach is to backpropagate (BP) a custom relevance score using modified rules, rather than the gradient. We analyze…

Machine Learning · Computer Science 2024-02-20 Leon Sixt , Maximilian Granz , Tim Landgraf

Depending on the Higgs-boson and top-quark masses, $M_H$ and $M_t$, the effective potential of the {\bf Standard Model} can develop a non-standard minimum for values of the field much larger than the weak scale. In those cases the standard…

High Energy Physics - Phenomenology · Physics 2007-05-23 M. Quirós

We study the implementation of a Topic Model algorithm in four-top searches at the LHC as a test-probe of a not ideal system for applying this technique. We study this Topic Model behavior as its different hypotheses such as mutual…

High Energy Physics - Phenomenology · Physics 2020-03-16 Ezequiel Alvarez , Federico Lamagna , Manuel Szewc

With the Higgs search program already quite mature, there is the exciting possibility of discovering a new particle with rates near that of the SM Higgs. We consider models with a signal in $\gamma \gamma$ below the SM Higgs mass, taking…

High Energy Physics - Phenomenology · Physics 2018-08-29 Patrick J. Fox , Neal Weiner

We consider the problem of classification in a comparison-based setting: given a set of objects, we only have access to triplet comparisons of the form "object $x_i$ is closer to object $x_j$ than to object $x_k$." In this paper we…

Machine Learning · Statistics 2019-05-30 Michaël Perrot , Ulrike von Luxburg

Capturing complex dependence structures between outcome variables (e.g., study endpoints) is of high relevance in contemporary biomedical data problems and medical research. Distributional copula regression provides a flexible tool to model…

Methodology · Statistics 2022-02-28 Nicolai Hans , Nadja Klein , Florian Faschingbauer , Michael Schneider , Andreas Mayr

We explore the usage of boosted as well as semi-boosted topologies in all-hadronic $t\bar{t}$ final states in simulated $pp$ collisions at $\sqrt{s} = 14\,$TeV, with top quarks decaying into a boosted hadronic top-jet or a $W$-jet and an…

High Energy Physics - Phenomenology · Physics 2024-11-08 Jiri Kvita

In a recent study by Dittmar and Dreiner it was shown that with appropriate selection cuts the signature of events containing two charged leptons and missing energy represents the best chance of detecting the Standard Model Higgs scalar in…

High Energy Physics - Phenomenology · Physics 2008-11-26 S. Moretti

We present Diffusion Model Patching (DMP), a simple method to boost the performance of pre-trained diffusion models that have already reached convergence, with a negligible increase in parameters. DMP inserts a small, learnable set of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Seokil Ham , Sangmin Woo , Jin-Young Kim , Hyojun Go , Byeongjun Park , Changick Kim

Although recent Higgs data from ATLAS and CMS are compatible with a Standard Model (SM) signal at $2\sigma$ level, both experiments see indications for an excess in the diphoton decay channel, which points to new physics beyond the SM.…

High Energy Physics - Phenomenology · Physics 2015-06-12 Wei Chao , Jian-Hui Zhang , Yongchao Zhang

We study the boosted Higgs tagging using the Lund jet plane. The convolutional neural network is used for the Lund images data set to classify hadronically decaying Higgs from the QCD background. We consider $H\to b \bar{b}$ and $H \to gg$…

High Energy Physics - Phenomenology · Physics 2022-01-19 Charanjit K. Khosa

Determining the form of the Higgs potential is one of the most exciting challenges of modern particle physics. Higgs pair production directly probes the Higgs self-coupling and should be observed in the near future at the High-Luminosity…

High Energy Physics - Phenomenology · Physics 2024-11-15 Radha Mastandrea , Benjamin Nachman , Tilman Plehn
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