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    ML4Jets 2026

    14–18 Sept 2026
    Europe/Vienna timezone

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    Session

    Plenary Presentations

    14 Sept 2026, 09:30

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    1. 151. Experimental Overview
      Nicole Michelle Hartman (TUM (DE))
      14/09/2026, 09:30

      TBA

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    2. 152. Theory Overview
      Ben Assi, Ben Assi, Benoit Assi
      14/09/2026, 10:00

      TBA

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    3. 153. Event Generation Overview
      Theo Heimel (UCLouvain)
      15/09/2026, 09:00

      TBA

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    4. 156. Overview of the Application of Generative Models to Fast Simulation in Large HEP Experiments
      Michał Mazurek (National Centre for Nuclear Research (PL))
      15/09/2026, 09:30

      Monte Carlo simulations are essential for physics analyses and detector design in High Energy Physics (HEP). As the computational requirements of traditional simulation rapidly outpace available computing budgets, leveraging Generative AI for fast simulation has become vital to producing the required volume of simulated samples.
      Nevertheless, transitioning from initial, toy models to...

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    5. 157. SBI Overview
      Jay Ajitbhai Sandesara
      15/09/2026, 10:00

      TBA

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    6. 155. Overview Foundation Models
      Anna Hallin (University of Hamburg), Anna Maria Cecilia Hallin (Universität Hamburg)
      16/09/2026, 09:00

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    7. 118. From Prompts to Publications: Agentic AI for Collider Analysis
      Eric Anton Moreno (Massachusetts Inst. of Technology (US))
      16/09/2026, 09:30

      Experimental high energy physics analysis is traditionally a multi-year effort dominated by repetitive implementation that demands little physics insight. LLM-based AI agents can now autonomously execute substantial portions of this pipeline, collapsing the implementation bottleneck to roughly ten hours of wall-clock time. This talk surveys the rapidly developing landscape of agentic AI in...

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    8. 150. Anomaly Detection: From Methods to Applications
      Marie Hein (RWTH Aachen University)
      17/09/2026, 09:00

      Traditional new-physics searches face a trade-off between coverage and sensitivity. Anomaly detection offers a way to extend their reach by searching for unusual signatures without assuming a specific signal model. Over the past decade, the field has developed a broad range of anomaly-detection paradigms and methods. More recently, the focus has begun to shift from developing new methods...

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    9. 154. Fast AI / Trigger Overview
      Sioni Paris Summers (CERN)
      17/09/2026, 09:30

      TBA

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    10. 158. GPU-deployment in online reconstruction at ALICE
      Felix Weiglhofer (CERN)
      18/09/2026, 09:00

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    11. 41. Machine Learning for Hadronization
      Manuel Szewc
      18/09/2026, 09:30

      Hadronization, the transition between unobservable quarks and gluons to observable hadrons, is a key aspect of the theoretical framework of particle physics. However, it is a fundamentally challenging process due to its non-pertubative nature, and thus event generators implement empirical models based on QCD insights. In this talk, I'll detail how Machine Learning has been incorporated into...

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