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The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as $top$ $tagging$, is a crucial component in many measurements of Standard Model processes and searches for beyond the…

High Energy Physics - Experiment · Physics 2024-12-16 ATLAS Collaboration

Additive manufacturing (AM) continues to transform modern manufacturing by enabling flexible, on-demand production of complex geometries across diverse industries. Fused filament fabrication (FFF) has extended AM to laboratories,…

Machine Learning · Computer Science 2026-05-06 Ahmadreza Eslaminia , Chuhan Cai , Cameron Smith , Ruo-Syuan Mei , Shichen Li , Rajiv Malhotra , Klara Nahrstedt , Chenhui Shao

Jet substructure has provided new opportunities for searches and measurements at the LHC, and has seen continuous development since the optimization of the large-radius jet definition used by ATLAS was performed during Run 1. A range of new…

High Energy Physics - Experiment · Physics 2021-05-05 ATLAS Collaboration

Detecting multiple planes in images is a challenging problem, but one with many applications. Recent work such as J-Linkage and Ordered Residual Kernels have focussed on developing a domain independent approach to detect multiple…

Computer Vision and Pattern Recognition · Computer Science 2013-12-30 Prateek Singhal , Aditya Deshpande , N Dinesh Reddy , K Madhava Krishna

The search for heavy $W'$ bosons in their decay modes to a lepton and a heavy neutrino offers a promising avenue for probing new physics beyond the Standard Model. This work focuses on such a signature with an energetic lepton plus a fat…

High Energy Physics - Phenomenology · Physics 2025-03-27 Songshaptak De , Atri Dey , Tousik Samui

The Parameter-Efficient Fine-Tuning (PEFT) methods have been extensively researched for large language models in downstream tasks. Among all the existing approaches, the Low-Rank Adaptation (LoRA) has gained popularity for its streamlined…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Tangyu Jiang , Haodi Wang , Chun Yuan

This paper introduces a novel tree-based model, Learning Hyperplane Tree (LHT), which outperforms state-of-the-art (SOTA) tree models for classification tasks on several public datasets. The structure of LHT is simple and efficient: it…

Machine Learning · Computer Science 2025-01-16 Hongyi Li , Jun Xu , William Ward Armstrong

We present a technique for translating a black-box machine-learned classifier operating on a high-dimensional input space into a small set of human-interpretable observables that can be combined to make the same classification decisions. We…

High Energy Physics - Phenomenology · Physics 2021-04-21 Taylor Faucett , Jesse Thaler , Daniel Whiteson

We propose a differentiable vertex fitting algorithm that can be used for secondary vertex fitting, and that can be seamlessly integrated into neural networks for jet flavour tagging. Vertex fitting is formulated as an optimization problem…

High Energy Physics - Experiment · Physics 2023-10-20 Rachel E. C. Smith , Inês Ochoa , Rúben Inácio , Jonathan Shoemaker , Michael Kagan

The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in…

High Energy Physics - Experiment · Physics 2023-09-15 The H1 collaboration , V. Andreev , M. Arratia , A. Baghdasaryan , A. Baty , K. Begzsuren , A. Bolz , V. Boudry , G. Brandt , D. Britzger , A. Buniatyan , L. Bystritskaya , A. J. Campbell , K. B. Cantun Avila , K. Cerny , V. Chekelian , Z. Chen , J. G. Contreras , J. Cvach , J. B. Dainton , K. Daum , A. Deshpande , C. Diaconu , A. Drees , G. Eckerlin , S. Egli , E. Elsen , L. Favart , A. Fedotov , J. Feltesse , M. Fleischer , A. Fomenko , C. Gal , J. Gayler , L. Goerlich , N. Gogitidze , M. Gouzevitch , C. Grab , T. Greenshaw , G. Grindhammer , D. Haidt , R. C. W. Henderson , J. Hessler , J. Hladký , D. Hoffmann , R. Horisberger , T. Hreus , F. Huber , P. M. Jacobs , M. Jacquet , T. Janssen , A. W. Jung , J. Katzy , C. Kiesling , M. Klein , C. Kleinwort , H. T. Klest , R. Kogler , P. Kostka , J. Kretzschmar , D. Krücker , K. Krüger , M. P. J. Landon , W. Lange , P. Laycock , S. H. Lee , S. Levonian , W. Li , J. Lin , K. Lipka , B. List , J. List , B. Lobodzinski , O. R. Long , E. Malinovski , H. -U. Martyn , S. J. Maxfield , A. Mehta , A. B. Meyer , J. Meyer , S. Mikocki , V. M. Mikuni , M. M. Mondal , K. Müller , B. Nachman , Th. Naumann , P. R. Newman , C. Niebuhr , G. Nowak , J. E. Olsson , D. Ozerov , S. Park , C. Pascaud , G. D. Patel , E. Perez , A. Petrukhin , I. Picuric , D. Pitzl , R. Polifka , S. Preins , V. Radescu , N. Raicevic , T. Ravdandorj , P. Reimer , E. Rizvi , P. Robmann , R. Roosen , A. Rostovtsev , M. Rotaru , D. P. C. Sankey , M. Sauter , E. Sauvan , S. Schmitt , B. A. Schmookler , G. Schnell , L. Schoeffel , A. Schöning , F. Sefkow , S. Shushkevich , Y. Soloviev , P. Sopicki , D. South , A. Specka , M. Steder , B. Stella , U. Straumann , C. Sun , T. Sykora , P. D. Thompson , F. Torales Acosta , D. Traynor , B. Tseepeldorj , Z. Tu , G. Tustin , A. Valkárová , C. Vallée , P. Van Mechelen , D. Wegener , E. Wünsch , J. Žáček , J. Zhang , Z. Zhang , R. Žlebčík , H. Zohrabyan , F. Zomer

While deep learning has reduced the prevalence of manual feature extraction, transformation of data via feature engineering remains essential for improving model performance, particularly for underwater acoustic signals. The methods by…

Jet tagging is a classification problem in high-energy physics experiments that aims to identify the collimated sprays of subatomic particles, jets, from particle collisions and tag them to their emitter particle. Advances in jet tagging…

High Energy Physics - Phenomenology · Physics 2024-06-14 Yash Semlani , Mihir Relan , Krithik Ramesh

Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning methods are able to outperform classical Machine Learning algorithms. One popular Deep Learning architecture in HAR is the DeepConvLSTM. In this paper we…

Human-Computer Interaction · Computer Science 2023-04-03 Marius Bock , Alexander Hoelzemann , Michael Moeller , Kristof Van Laerhoven

Automatic modulation recognition (AMR) is a promising technology for intelligent communication receivers to detect signal modulation schemes. Recently, the emerging deep learning (DL) research has facilitated high-performance DL-AMR…

Signal Processing · Electrical Eng. & Systems 2021-10-12 Fuxin Zhang , Chunbo Luo , Jialang Xu , Yang Luo

Jet interactions in a hot QCD medium created in heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet observables with respect to the proton-proton baseline. However, the steeply falling…

High Energy Physics - Phenomenology · Physics 2021-04-01 Yi-Lun Du , Daniel Pablos , Konrad Tywoniuk

The rapid adoption of Large Language Models (LLMs) has raised significant environmental concerns. Unlike the one-time cost of training, LLM inference occurs continuously and dominates the AI energy footprint. Yet most sustainability studies…

Machine Learning · Computer Science 2026-04-08 Hemang Jain , Shailender Goyal , Divyansh Pandey , Karthik Vaidhyanathan

This paper introduces a new architecture for human pose estimation using a multi- layer convolutional network architecture and a modified learning technique that learns low-level features and higher-level weak spatial models. Unconstrained…

Computer Vision and Pattern Recognition · Computer Science 2014-04-24 Arjun Jain , Jonathan Tompson , Mykhaylo Andriluka , Graham W. Taylor , Christoph Bregler

The jets are the final state manifestation of the hard parton scattering. Since at LHC energies the production of hard processes in proton-proton collisions will be copious and varied, it is important to develop methods to identify them…

High Energy Physics - Experiment · Physics 2009-12-07 Antonio Ortiz , Guy Paic

A leading family of algorithms for state estimation in dynamic systems with multiple sub-states is based on particle filters (PFs). PFs often struggle when operating under complex or approximated modelling (necessitating many particles)…

Signal Processing · Electrical Eng. & Systems 2024-08-22 Itai Nuri , Nir Shlezinger