| Accueil > CERN Experiments > LHC Experiments > ATLAS > ATLAS Preprints > Classifying hadronic objects in ATLAS with ML/AI algorithms |
| ATLAS Slides | |
| Report number | ATL-PHYS-SLIDE-2025-416 |
| Title | Classifying hadronic objects in ATLAS with ML/AI algorithms |
| Author(s) | Toffolin, Leonardo (Universita e INFN Trieste (IT)) |
| Corporate author(s) | The ATLAS collaboration |
| Collaboration | ATLAS Collaboration |
| Submitted to | The 32nd International Symposium on Lepton Photon Interactions at High Energies (Lepton Photon 2025), Madison, Wisconsin, Us, 25 - 29 Aug 2025 |
| Submitted by | leonardo.toffolin@cern.ch on 31 Aug 2025 |
| Subject category | Particle Physics - Experiment |
| Accelerator/Facility, Experiment | CERN LHC ; ATLAS |
| Free keywords | JETETMISS ; BTAGGING ; Object identification ; Machine Learning ; Transformers ; JETETMISS |
| Abstract | Hadronic object reconstruction and classification is one of the most promising settings for cutting-edge machine learning and artificial intelligence algorithms at the LHC. In this contribution, highlights of ML/AI applications by ATLAS to QCD and boosted-object identification, MET reconstruction and other tasks will be presented. |