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6th Inter-experiment Machine Learning Workshop

from Monday 29 January 2024 (09:00) to Friday 2 February 2024 (19:00)
CERN (503/1-001)

        : Sessions
    /     : Talks
        : Breaks
29 Jan 2024
30 Jan 2024
31 Jan 2024
1 Feb 2024
2 Feb 2024
AM
10:00
Keynotes Physics + ML (until 11:00) (40/S2-D01 - Salle Dirac)
10:00 ML and Quantum Physics - Eliska Greplova (TU Delft)  
11:00 --- Coffee Break ---
11:30
Contributed Talks (until 12:50) (40/S2-D01 - Salle Dirac)
11:30 Accelerating Graph-Based Tracking with Symbolic Regression - Nathalie Soybelman (Weizmann Institute of Science (IL))  
11:50 Reinforcement Learning Algorithms for Charged Particle Tracking with Applications in Proton Computed Tomography - Tobias Kortus  
12:10 Differentiable Vertex Fitting for Jet Flavour Tagging - Rachel Emma Clarke Smith (SLAC National Accelerator Laboratory (US)) Ruben Miguel De Almeida Inacio (LIP - Laboratorio de Instrumentação e Física Experimental de Partículas (PT))  
12:30 Advances in developing deep neural networks for finding primary vertices in proton-proton collisions at the LHC - Simon Akar (University of Cincinnati (US))  
09:00
Keynotes Physics + ML (until 10:30)
09:00 Improving data-driven model predictions using physics in the CERN accelerator complex - Francesco Maria Velotti (CERN)  
IML2024_Velotti.mp4
Slides
PDF version (not for presentation)
09:30 ML and Molecular Physics - Jonas Koehler (Microsoft Research)  
10:30 --- Coffee Break ---
11:00
CERN Data Science Seminar (until 12:00)
11:00 Problem solving as a translation task - Francois Charton (Facebook AI Research)  
09:00
Tutorials (until 10:30)
09:00 Quantum machine learning - Dr Sofia Vallecorsa (CERN)  
10:30 --- Coffee ---
11:00
Tutorials (until 12:30)
11:00 Thinking like Transformers - Dr Gail Weiss (EPFL)  
09:00
Contributed Talks (until 10:20) (222/R-001)
09:00 DeepTreeGANv2: Iterative Pooling of Point Clouds - Mr Moritz Scham (Deutsches Elektronen-Synchrotron (DE))  
09:20 Out-of-Distribution Multi-set Generation with Context Extrapolation for Amortized Simulation and Inverse Problems - Hosein Hashemi (LMU Munich)  
09:40 Conditional Set-to-Set Generation for Fast Simulation using Diffusion and Graph-to-Graph Translation - Dmitrii Kobylianskii (Weizmann Institute of Science (IL))  
10:00 Unweighted event generation with matrix element surrogates - Timo Janssen  
10:20 --- Coffee ---
10:50
Contributed Talks (until 11:50) (222/R-001)
10:50 A Deep Generative Model for Hadronization - Jay Chan (Lawrence Berkeley National Laboratory)  
11:10 Reinforcement learning for automatic data quality monitoring in HEP experiments - Olivia Jullian Parra (CERN)  
11:30 Longitudinal Beam Diagnostics and Phase Space Reconstruction in the LHC Using ML - Konstantinos Iliakis (CERN)  
11:50 Closeout   (222/R-001)
PM
14:00 Workshop welcome and introduction - Julian Garcia Pardinas (CERN)  
14:05
Keynotes ML Research (until 16:05)
14:05 Thoughts about Machine Learning - Prof. Juergen Schmidhuber (KAUST and IDSIA)  
15:05 Modeling epistemics with machine learning - Dr Gael Varoquaux (INRIA)  
16:05 --- Coffee Break ---
16:30
Contributed Talks (until 17:50)
16:30 Attention to the strengths of physics interactions: Enhanced Deep Learning Event Classification for Particle Physics Experiments - Polina Moskvitina (Nikhef National institute for subatomic physics (NL))  
16:50 Modeling $N_{\mathrm{ch}}$ distributions and $p_{\mathrm{T}}$ spectra in high-energy pp collisions with DNNs - Maria Alejandra Calmon Behling (Goethe University Frankfurt (DE))  
17:10 The DL Advocate: Playing the devil's advocate with hidden systematic uncertainties - Andrea Mauri (Imperial College (GB))  
17:30 the Fair Universe project and the HiggsML Uncertainty Challenge - David Rousseau (IJCLab-Orsay)  
12:50 --- Lunch ---
14:00
Contributed Talks (until 15:20) (40/S2-D01 - Salle Dirac)
14:00 End-to-end Reconstruction Algorithm for Highly Granular Calorimeters - Mr Philipp Zehetner (Ludwig Maximilians Universitat (DE))  
14:20 Electron and Proton Classification with AMS ECAL Using Convolutional Vision Transformers and Domain Adaptation - Berk Turk (Middle East Technical University (TR))  
14:40 Parametrising profiled likelihoods with neural networks - Dr Humberto Reyes-González (University of Genoa)  
15:00 Accelerating the search for mass bumps using the Data-Directed Paradigm - Bruna Pascual (Universite de Montreal (CA))  
15:20 --- Coffee Break ---
15:50
Contributed Talks (until 17:50) (40/S2-D01 - Salle Dirac)
15:50 Training and optimisation of large transformer models at CERN: an ATLAS case study on Kubeflow - Maxence Draguet (University of Oxford (GB))  
16:10 Masked particle modelling - Samuel Byrne Klein (Universite de Geneve (CH))  
16:30 Finetuning Foundation Models for Joint Analysis Optimization - Matthias Vigl (Technische Universitat Munchen (DE))  
16:50 Re-simulation-based self-supervision for representation learning - Jeffrey Krupa (Massachusetts Institute of Technology)  
12:00 --- Lunch ---
14:00
Keynote Industry (until 15:00)
14:00 Retrieval Augmented Language Models - Casey Fitzpatrick (Contextual AI)  
15:00 --- Coffee ---
15:30
Poster Session (until 18:55)
15:30 Machine learning approaches for parameter reweighting in MC samples of top quark production in CMS - Valentina Guglielmi (Deutsches Elektronen-Synchrotron (DE))  
15:35 ML-assisted reconstruction of hadron-collider events with mini-jets - Josef Modestus Murnauer (Max Planck Society (DE))  
15:40 Deep learning for the rare top decay t→sW at the LHC - Jeewon Heo (University of Seoul, Department of Physics (KR))  
15:45 Improving the line-segment tracking algorithm with machine learning for the High Luminosity LHC - Jonathan Guiang (Univ. of California San Diego (US))  
15:50 A data-driven and model-agnostic approach to solving combinatorial assignment problems in searches for new physics - Anthony Badea (University of Chicago (US)) Javier Montejo Berlingen (The Barcelona Institute of Science and Technology (BIST) (ES))  
15:55 DeepCore2.0: Convolutional Neural Network for Tracking in the Core of High-Energy Jets - Hichem Bouchamaoui (Princeton University (US))  
16:00 Topological separation of dielectron signals using machine learning in Pb--Pb collisions with ALICE - Jerome Jung (Goethe University Frankfurt (DE))  
16:05 Model-independent strategy for New Physics seartch at LHC using Anomaly Detection algorithms - Louis Vaslin (High Energy Accelerator Research Organization (JP))  
16:10 Electron identification with a convolutional neural network - Hoang Dai Nghia Nguyen (Université de Montreal (CA))  
16:15 Particle identification with Machine Learning for ALICE ITS2 - Giorgio Alberto Lucia (Universita e INFN Torino (IT))  
16:20 Decorrelation using Optimal Transport - Malte Algren (Universite de Geneve (CH))  
16:25 Particle Transformer for tau lepton pair invariant mass reconstruction for the HH→bbtautau CMS analysis - Valentina Camagni (Universita & INFN, Milano-Bicocca (IT))  
16:30 Apples to Apples in Jet Quenching - João A. Gonçalves (LIP - IST)  
16:35 Uncertainty-aware Machine Learning for Proton Therapy Range Verification with a Digital Tracking Calorimeter - Alexander Schilling (University of Applied Sciences Worms)  
16:40 Training and optimisation of large transformer models at CERN: an ATLAS case study on Kubeflow - Poster - Maxence Draguet (University of Oxford (GB))  
16:45 Reinforcement Learning Algorithms for Charged Particle Tracking with Applications in Proton Computed Tomography - Poster - Tobias Kortus  
16:50 Out-of-Distribution Multi-set Generation with Context Extrapolation for Amortized Simulation and Inverse Problems - Poster - Hosein Hashemi (LMU Munich)  
16:55 Electron and Proton Classification with AMS ECAL Using Convolutional Vision Transformers and Domain Adaptation - Poster - Berk Turk (Middle East Technical University (TR))  
17:00 Differentiable Vertex Fitting for Jet Flavour Tagging - Poster - Ruben Miguel De Almeida Inacio (LIP - Laboratorio de Instrumentação e Física Experimental de Partículas (PT))  
17:05 Modeling $N_{\mathrm{ch}}$ distributions and $p_{\mathrm{T}}$ spectra in high-energy pp collisions with DNNs - Poster - Maria Alejandra Calmon Behling (Goethe University Frankfurt (DE))  
17:10 DeepTreeGANv2: Iterative Pooling of Point Clouds - Poster - Mr Moritz Scham (Deutsches Elektronen-Synchrotron (DE))  
17:15 Accelerating the search for mass bumps using the Data-Directed Paradigm - Poster - Bruna Pascual (Universite de Montreal (CA))  
17:20 A Deep Generative Model for Hadronization - Poster - Jay Chan (Lawrence Berkeley National Laboratory)  
17:25 Attention to the strengths of physics interactions: Enhanced Deep Learning Event Classification for Particle Physics Experiments - Poster - Polina Moskvitina (Nikhef National institute for subatomic physics (NL))  
17:30 Longitudinal Beam Diagnostics and Phase Space Reconstruction in the LHC Using ML - Poster - Konstantinos Iliakis (CERN)  
12:30 --- Lunch ---
14:00
Keynotes Physics + ML (until 15:00)
14:00 Collider Physics and ML - Gregor Kasieczka (Hamburg University (DE))  
15:00 --- Coffee ---
15:30
Poster Session (until 18:30)
15:30 Simultaneous calibration of jet energy and mass using DNN in ATLAS - Pierre Antoine Delsart (LPSC/CNRS (Grenoble, FR))  
15:35 Search for long-lived heavy neutral leptons using a displaced jet tagger - Matthias Komm (Deutsches Elektronen-Synchrotron (DE))  
15:40 Transformers for Particle Track Reconstruction and Hit Clustering - Nadezhda Dobreva  
15:45 Simulation-based inference in the search for CP violation in leptonic WH production - Ricardo Barrué (LIP - Laboratorio de Instrumentacao e Fisica Experimental de Partículas)  
15:50 Conditional normalizing flows for correcting simulations - Caio Cesar Daumann (Rheinisch Westfaelische Tech. Hoch. (DE))  
15:55 Unsupervised tagging of semivisible jets with energy-based autoencoders in CMS - Florian Eble (ETH Zurich (CH))  
16:00 Energy-based graph autoencoders for semivisible jet tagging in the Lund representation - Christoph Frederik Ribbe (ETH Zurich (CH))  
16:05 Systematic Effects in Jet Tagging Performance for the ATLAS Detector - Kevin Thomas Greif (University of California Irvine (US))  
16:10 BSM models and parameter inference via an n-channel 1D-CNN - Yong Sheng Koay  
16:15 Generating parton-level events from reconstructed events with Conditional Normalizing Flows - Adrian Antonio Petre (ETH Zurich (CH))  
16:20 Machine learning for enhanced measurement of Higgs boson production cross section via vector boson fusion in H->WW* with the ATLAS detector - Metea Castilleja Marr (Simon Fraser University (CA))  
16:25 The DL Advocate: Playing the devil's advocate with hidden systematic uncertainties - Poster - Guillermo Hijano Mendizabal (University of Zurich (CH))  
16:30 Unweighted event generation with matrix element surrogates - Poster - Timo Janssen  
16:35 the Fair Universe project and the HiggsML Uncertainty Challenge - Poster - Ragansu Chakkappai (Université Paris-Saclay (FR))  
16:40 Reinforcement learning for automatic data quality monitoring in HEP experiments - Poster - Olivia Jullian Parra (CERN)  
16:45 Re-simulation-based self-supervision for representation learning - Poster - Jeffrey Krupa (Massachusetts Institute of Technology)  
16:50 Parametrising profiled likelihoods with neural networks - Poster - Dr Humberto Reyes-González (University of Genoa)  
16:55 End-to-end Reconstruction Algorithm for Highly Granular Calorimeters - Poster - Mr Philipp Zehetner (Ludwig Maximilians Universitat (DE))  
17:00 Masked particle modelling - Poster - Samuel Byrne Klein (Universite de Geneve (CH))  
17:05 Finetuning Foundation Models for Joint Analysis Optimization - Poster - Matthias Vigl (Technische Universitat Munchen (DE))  
17:10 Advances in developing deep neural networks for finding primary vertices in proton-proton collisions at the LHC - Poster - Simon Akar (University of Cincinnati (US))  
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