"ML at HEP workshop" in Japan 2024

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A data-driven and model-agnostic approach to solving combinatorial assignment problems in searches for new physics

A Machine-learning Approach to Assessing the Presence of Substructure in Quasar-host Galaxies

AI Methods in Galaxy Formation

Closing

Cosmosage: a natural-language assistant for cosmology

Dark Matter Applications of Machine Learning

Data Science for Astronomy

Development of a hardware trigger using machine learning in the Belle II experiment

Development of Anomaly Detection techniques applied to the building and Quality Control of ATLAS new silicon tracking detector

Extracting optimal information from upcoming cosmological surveys

Flow-Matching models for the LHC

Improving the diphoton event selection with GNNs

Jet Classification using High-Level Features from Anatomy of Top Jets

Machine-learning-assisted beam tuning at the KEK Linac and prospects for SuperKEKB

ML for Jet Tagging: Status and Prospects

Model-independence of machine-learning-based mass reconstruction for inclusive multi-jet search

Multi-Scale Cross-Attention Transformer Encoder for Event Classification

Opening

Pre-training strategy using real particle collision data for event classification in collider physics

Prospects of LLMs for Fundamental Physics

Returning CP-observables to the frames they belong (unfolding)

Review and Perspective on AI for Observational Cosmology

Review: Low-level object reconstruction and simulation using ML

Using AI for unsupervised discovery in particle physics

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09/01/2024

10/01/2024

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