Name: ML4Jets2023
Start: 2023-11-06T08:30:00+01:00
End: 2023-11-10T16:00:00+01:00
Location: DESY

ML4Jets2023

from Monday 6 November 2023 (08:30) to Friday 10 November 2023 (16:00)

Monday 6 November 2023

08:30 Arrival and Coffee
Arrival and Coffee
08:30 - 09:15
Room: Main Auditorium
09:15 Opening
Opening
09:15 - 10:30
Room: Main Auditorium
Contributions

09:15 Welcome and Logistics

09:30 Experimental Introducton - Kevin Pedro (Fermi National Accelerator Lab. (US))

10:00 Modern Machine Learning for the LHC Simulation Chain - Ramon Winterhalder (UCLouvain)
10:30 Coffee
Coffee
10:30 - 11:00
Room: Main Auditorium
11:00
11:00 - 12:30
Room: Seminarraum 4a/b
Contributions

11:00 Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows - Thorsten Buss (Universität Hamburg (DE))

11:15 Pushing Normalizing Flows for higher-dimensional Detector Simulations - Florian Ernst

11:30 Attention to Mean Fields for Particle Cloud Generation - Benno Kach (Deutsches Elektronen-Synchrotron (DE))

11:45 Latent Generative Models for Fast Calorimeter Simulation - Qibin Liu (Tsung-Dao Lee Institute (CN) & Shanghai Jiao Tong University (CN))

12:00 New Angles on Fast Calorimeter Shower Simulation - Peter McKeown

12:15 Improved selective background Monte Carlo simulation at Belle II with graph attention networks and weighted events - Boyang Yu
11:00 - 12:30
Room: Main Auditorium
Contributions

11:00 Reconstructing and calibrating hadronic objects with ML/AI algorithms in ATLAS - Tobias Fitschen (University of Manchester (GB))

11:15 Boosted Jet Tagging and Calibration in CMS - Oz Amram (Fermi National Accelerator Lab. (US))

11:30 Vertex Reconstruction with Transformers - Nikita Ivvan Pond (University of London (GB))

11:45 Performance of heavy flavour jet identification in boosted topologies in CMS 13 TeV data - Matteo Marchegiani (ETH Zurich (CH))

12:00 Towards Novel Charged Particle Tracking Approaches with Transformer and U-Net Models - Zef Wolffs (Nikhef National institute for subatomic physics (NL))
12:30 Lunch
Lunch
12:30 - 14:00
Room: Main Auditorium
14:00
14:00 - 15:30
Room: Seminarraum 4a/b
Contributions

14:00 Event Reconstruction with GNNs at the FCC - Dolores Garcia (CERN)

14:15 Time-of-Flight Estimation using Machine Learning Techniques - Konrad Helms

14:30 Set2Tree: Particle decay reconstruction via GNN - Dmitrii Kobylianskii (Weizmann Institute of Science (IL))

14:45 End-to-end analysis with jointly optimized particle identification and analysis optimization objectives - Matthias Vigl (Technische Universitat Munchen (DE))

15:00 ν²-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows - Johnny Raine (Universite de Geneve (CH)) Matthew Leigh (University of Geneva)

15:15 Reconstructing ALP properties and optimizing experimental design with simulation-based inference - Alessandro Morandini
14:00 - 15:30
Room: Main Auditorium
Contributions

14:00 Regression-based refinement of fast simulation - Moritz Jonas Wolf (Hamburg University (DE))

14:15 Refining Fast Calorimeter Simulations with a Schrödinger Bridge - Sascha Diefenbacher (Lawrence Berkeley National Lab. (US))

14:30 SuperCalo: Calorimeter shower super-resolution - Ian Pang

14:45 Denoising Graph Super-Resolution with Diffusion Models and Transformers for Improved Particle Reconstruction - Nilotpal Kakati (Weizmann Institute of Science (IL))

15:00 SR-GAN for SR-gamma: photon super resolution at collider experiments - Florian Alexander Mausolf (Rheinisch Westfaelische Tech. Hoch. (DE))
15:30 Coffee
Coffee
15:30 - 16:00
Room: Main Auditorium
16:00
16:00 - 18:15
Room: Main Auditorium
Contributions

16:00 Generic representations of jets at detector-level with self supervised learning - Etienne Dreyer (Weizmann Institute of Science (IL))

16:15 CoCo: Contrastive Combinatorics - Debajyoti Sengupta (Universite de Geneve (CH))

16:30 Identifying semi-visible jets with darkCLR - Tanmoy Modak

16:45 Reconstructing full pp collision events with HGPflow - Nilotpal Kakati (Weizmann Institute of Science (IL))

17:30 Scalable neural network models and terascale datasets for particle-flow reconstruction - Joosep Pata (National Institute of Chemical Physics and Biophysics (EE))

17:45 Masked particle modelling - Matthew Leigh (University of Geneva)

18:00 ML-assisted reconstruction of hadron-collider events with mini-jets - Josef Modestus Murnauer (Max Planck Society (DE))
18:30 Reception
Reception
18:30 - 20:30
Room: Kantine-Anbau
Tuesday 7 November 2023
09:00
09:00 - 10:30
Room: Main Auditorium
Contributions

09:00 Deep learning methods for noise filtering in the NA61/SHINE experiment - Marcin Slodkowski (Warsaw University of Technology (PL))

09:15 The application of neural networks for the calibration of topological cell clusters in the ATLAS calorimeters - Peter Loch (University of Arizona (US))

09:30 Jets as sets or graphs: Fast jet classification on FPGAs for efficient triggering at the HL-LHC - Denis-Patrick Odagiu (ETH Zurich (CH))

09:45 A Convolutional Neural Network for topological fast selection algorithms in FPGAs for the HL-LHC upgrade of the CMS experimen - Maciej Mikolaj Glowacki (University of Bristol (GB))

10:00 Realtime Anomaly Detection in the CMS Experiment Global Trigger Test Crate - Jannicke Pearkes (University of Colorado Boulder (US))

10:15 LLPNet: Graph Autoencoder for Triggering Light Long-Lived Particles at HL-LHC - Prabhat Solanki (Indian Institute of Science, Bengaluru)
09:00 - 09:45
Room: Seminarraum 4a/b
Contributions

09:00 Learning a Representation of New Physics Models - Tore von Schwartz

09:15 Anatomy of Jet classification using deep learning - Sung Hak Lim (Rutgers University)

09:30 Hyperbolic Machine Learning for Jet Physics - Nathaniel Sherlock Woodward (Massachusetts Inst. of Technology (US))
10:30 Coffee
Coffee
10:30 - 11:00
Room: Main Auditorium
11:00
11:00 - 12:30
Room: Main Auditorium
Contributions

11:00 Fitting a deep generative hadronization model - Adam Kania (Jagiellonian University)

11:15 Fast Particle Cloud Generation with Flow Matching and Diffusion - Cedric Ewen

11:30 Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Information - Joschka Valentin Maria Birk

11:45 CaloPointFlow - Generating Calorimeter Showers as Point Clouds - Simon Schnake (DESY / RWTH Aachen University)

12:00 PC-Droid: Jet generation with diffusion - Debajyoti Sengupta (Universite de Geneve (CH))

12:15 DeepTreeGAN: Fast Generation of High Dimensional Point Clouds - Moritz Scham (Deutsches Elektronen-Synchrotron (DE))
12:30 Lunch
Lunch
12:30 - 14:00
Room: Main Auditorium
13:45
13:45 - 15:30
Room: Main Auditorium
Contributions

13:45 Conditional Set-to-Set Generation for Fast Simulation using Diffusion and Graph-to-Graph Translation - Nathalie Soybelman (Weizmann Institute of Science (IL))

14:00 CaloGraph: Calorimeter simulation via Graph-based diffusion model - Dmitrii Kobylianskii (Weizmann Institute of Science (IL))

14:15 High-Dimensional Diffusion Generative Models in Collider Physics - Vinicius Massami Mikuni (Lawrence Berkeley National Lab. (US))

14:30 CaloDiffusion with GLaM for High Fidelity Calorimeter Simulation - Kevin Pedro (Fermi National Accelerator Lab. (US))

14:45 Diffusion Models for the LHC - Sofia Palacios Schweitzer (ITP, University Heidelberg)

15:00 CaloClouds: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation - Erik Buhmann (Hamburg University (DE))

15:15 CaloLatent: Score-based Generative Modelling in the Latent Space for Calorimeter Shower Generation - Thandikire Madula (University College London)
14:00
14:00 - 15:30
Room: Seminarraum 4a/b
Contributions

14:00 Learning the language of QCD jets with transformers - Alexander Mück (RWTH Aachen University)

14:15 Off-Shell Processes from Neural Networks - Mathias Kuschick

14:30 High multiplicity with JetGPT - Jonas Spinner

14:45 Generate parton-level events from reconstructed events with Conditional Normalizing Flows - Davide Valsecchi (ETH Zurich (CH))

15:00 MEMeNNto – Matrix Element Method with Neural Networks - Nathan Huetsch (Institut für Theoretische Physik, Universität Heidelberg)

15:15 The MadNIS Reloaded - Theo Heimel (Heidelberg University)
15:30 Coffee
Coffee
15:30 - 16:00
Room: Main Auditorium
16:00
16:00 - 17:00
Room: Main Auditorium
Contributions

16:00 Keynote: Physics ex machina - Machine learning for fundamental physics - David Shih
17:00 Brezels
Brezels
17:00 - 17:30
Room: Main Auditorium

19:00 Public Film Preview and Public Discussion (in German, not part of ML4Jets - but you are invited)
Public Film Preview and Public Discussion (in German, not part of ML4Jets - but you are invited)
19:00 - 21:00
Room: Main Auditorium
Wednesday 8 November 2023
09:00
09:00 - 10:30
Room: Main Auditorium
Contributions

09:00 Machine Learning in Astrophysics and Astronomy - Caroline Heneka

09:30 Mapping Dark Matter in the Milky Way using Normalizing Flows and Gaia DR3 - Eric Putney (Rutgers, The State University of New Jersey)

09:45 Bayesian Insights into the high-redshift Universe with 21cmPIE-cINN - Benedikt Schosser (Heidelberg University) Theo Heimel (Heidelberg University)

10:00 PINNflation solving the dynamics of Inflation using Physics Informed Neural Nets - Lennart Röver (Heidelberg University)

10:15 ML Approach to Infer Galaxy Cluster Masses from eROSITA X-ray Images - Nicolas Barón Pérez
10:30 Coffee
Coffee
10:30 - 11:00
Room: Main Auditorium
11:00
11:00 - 11:30
Room: Main Auditorium
Contributions

11:00 The HEP-ML Living Review - Claudius Krause (Rutgers University) Johnny Raine (Universite de Geneve (CH)) Ramon Winterhalder (UC Louvain)

11:15 Open Data Detector: public dataset(s) for ML studies - Anna Zaborowska (CERN)
11:30
11:30 - 12:15
Room: Main Auditorium
Contributions

11:30 Evaluating Equivariance for Reconstruction - Savannah Thais

11:45 Constituent based Quark/Gluon Jet Tagging - Samuel Jankovych (Charles University (CZ))

12:00 Quark versus gluon tagging in CMS Open Data with CWoLa and TopicFlow - Ayodele Ore
12:15

12:15 - 12:30
Room: Main Auditorium

12:30 Lunch
Lunch
12:30 - 14:00
Room: Main Auditorium
14:00
14:00 - 15:30
Room: Main Auditorium
Contributions

14:00 ML for jets and beyond jets - Huilin Qu (CERN)

14:30 PELICAN Update: Equivariance, Explainability, and Robustness in Jet ML - Timothy Hoffman

14:45 Particle Transformer with built-in IRC safety - Congqiao Li (Peking University (CN))

15:00 Combining Energy Correlators with Machine Learning - Katherine Fraser (Harvard University)

15:15 SPECTER: Efficient Evaluation of the Spectral EMD - Rikab Gambhir (MIT)
15:30 Coffee
Coffee
15:30 - 16:00
Room: Main Auditorium
16:00
16:00 - 17:45
Room: Seminarraum 4a/b
Contributions

16:00 Back to the Roots: Tree-Based Algorithms for Weakly Supervised Anomaly Detection - Marie Hein (RWTH Aachen University)

16:15 Robust Anomaly Detection in the Presence of Irrelevant Features - Yik Chuen San

16:30 Drapes: Diffusion for weak supervision - Matthew Leigh (University of Geneva)

16:45 The Interplay of Machine Learning–based Resonant Anomaly Detection Methods - Radha Mastandrea (University of California, Berkeley)

17:00 Full Phase Space Resonant Anomaly Detection - Cedric Ewen

17:15 Combining resonant and tail-based anomaly detection - Gerrit Bickendorf (Universität Bonn)
16:00 - 17:30
Room: Main Auditorium
Contributions

16:00 Classifying the CP properties of the ggH coupling in H+2j production - Henning Bahl

16:15 Returning CP-Observables to the Frames they Belong - Jona Ackerschott

16:30 End-To-End Latent Variational Diffusion Models for Unfolding LHC Events - Kevin Thomas Greif (University of California Irvine (US))

16:45 Deep learning assisted unbinned measurements of jet substructure observables with the H1 detector - Vinicius Massami Mikuni (Lawrence Berkeley National Lab. (US))

17:00 Exploring the universality of jet quenching via Bayesian inference - Alexandre Falcão (University of Bergen)

17:15 Apples to Apples in Jet Quenching - João A. Gonçalves (LIP - Lisbon / IST - Universidade de Lisboa)
Thursday 9 November 2023
09:00
09:00 - 10:00
Room: Main Auditorium
Contributions

09:00 Non-resonant Anomaly Detection with Background Extrapolation - Kehang Bai (University of Oregon (US))

09:15 R-ANODE - Ranit Das (Rutgers University)

09:30 Anomaly Detection in Collider Physics via Factorized Observables - Raymond Wynne (MIT)

09:45 Unsupervised tagging of semivisible jets with normalized autoencoders in CMS - Florian Eble (ETH Zurich (CH))
10:00
10:00 - 10:30
Room: Main Auditorium
Contributions

10:00 Ultra-fast generation of Air Shower Images for Imaging Air Cherenkov Telescopes with Generative Adversarial Networks - Christian Elflein (Erlangen Centre for Astroparticle Physics)

10:15 ParticleGrow: Event by event simulation of heavy-ion collisions via autoregressive point cloud generation - Manjunath Omana Kuttan (Frankfurt Institute for Advanced Studies)
10:30 Coffee
Coffee
10:30 - 11:00
Room: Main Auditorium
11:00
11:00 - 12:30
Room: Main Auditorium
Contributions

11:00 caloutils - Utilities and Metrics for Generative Models of Calorimeter Showers - Moritz Scham (Deutsches Elektronen-Synchrotron (DE))

11:15 Understanding generative networks via classifier weight distributions - Luigi Favaro

11:30 Level up your performance calculation of the fast shower simulation model - Anna Zaborowska (CERN)

11:45 The New Physics Learning Machine: machine learning for goodness-of-fit via Neyman—Pearson testing - Marco Letizia (MaLGa Center, Università di Genova and INFN)

12:00 The Fast Calorimeter Simulation Challenge 2022 - Claudius Krause (Rutgers University)
12:30 Lunch
Lunch
12:30 - 14:00
Room: Main Auditorium
14:00
14:00 - 15:45
Room: Main Auditorium
Contributions

14:00 The DL Advocate: Playing the devil's advocate with hidden systematic uncertainties - Andrea Mauri (Imperial College (GB))

14:15 Systematic Effects in Jet Tagging Performance for the ATLAS Detector - Kevin Thomas Greif (University of California Irvine (US))

14:30 Evaluating Neural Network Uncertainty Estimation with Inconsistent Training Data - Giovanni De Crescenzo

14:45 Generalization Properties of Jet Classification - Sebastian Guido Bieringer (Hamburg University)

15:00 Deciphering the Structure of EFTs from String Theory using JAX and Reinforcement Learning - Andreas Schachner (Ludwig-Maximilians-Universität München)

15:15 Towards a phenomenological understanding of neural networks - Samuel Tovey (University of Stuttgart)

15:30 Machine Learning to Understand String Theory EFTs - Sven Krippendorf (LMU Munich)
15:45 Coffee
Coffee
15:45 - 16:15
Room: Main Auditorium
16:15
16:15 - 17:00
Room: Main Auditorium
Contributions

16:15 Cluster Scanning - Ivan Oleksiyuk (UNIGE)

16:30 Anomaly Detection in High Energy Physics via Non-Gaussian Variational Autoencoders - Thomas Dartnall Stern (University of Cape Town (ZA))

16:45 Quantum anomaly detection in the latent space of proton collision events at the LHC - Vasilis Belis (ETH Zurich (CH))
17:20
17:20 - 18:00
Contributions

17:20 Binary Discrimination at Next-to-Leading Order - Andrew Larkoski (UCLA)

17:25 Scalar Field Theories via Neural Networks at Initialization - Anindita Maiti (Perimeter Institute for Theoretical Physics)

17:30 Learning Broken Symmetries with Encouraged Invariance - Daniel Whiteson (University of California Irvine (US)) Edmund Witkowski (UCI)

17:35 HEP ML Lab — An end-to-end framework for signal vs background analysis in high energy physics - Jing Li (Dalian University of Technology, Liaoning, China)

17:40 Perturbatively Regularized Neural Networks - Chase Owen Shimmin (Yale University (US))
Friday 10 November 2023
09:00
09:00 - 10:30
Room: Main Auditorium
Contributions

09:00 Giving events a new shape : measurements of multijet event isotropy at ATLAS using optimal transport - Matt LeBlanc (University of Manchester (GB))

09:15 Sensitivity Studies for Search of B+ → K∗+ νν using Lorentz Equivariant Neural Networks at the Belle II Experiment - Caspar Schmitt

09:30 DeGeSim: Conditional Denoising Diffusion Probabilistic Models as Multi-Dimensional Density Mappers for Continuous and Discrete State Spaces - Judith Katzy (Deutsches Elektronen-Synchrotron (DE)) Stephen Jiggins (Deutsches Elektronen-Synchrotron (DE))

09:45 Jet formation with Chebyshev Polynomials - Henry Day-Hall (Czech Technical University in Prague (CZ))

10:00 Weakly supervised training for optimal transport pileup mitigation strategies at hadron colliders - Nathan Suri Jr (Yale University (US))

10:15 Model-agnostic search for dijet resonances with anomalous jet substructure with the CMS detector - Louis Moureaux (Hamburg University (DE))
10:30 Coffee
Coffee
10:30 - 11:00
Room: Main Auditorium
11:00
11:00 - 12:10
Room: Main Auditorium
Contributions

11:00 Theory Closure - Michael Kramer (Rheinisch Westfaelische Tech. Hoch. (DE))

11:30 Closing and Final Remarks - Gregor Kasieczka (Hamburg University (DE))

11:35 Announcement of ML4Jets 2024

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