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

ML4Jets2023

from Monday, November 6, 2023 (8:30 AM) to Friday, November 10, 2023 (4:00 PM)

Monday, November 6, 2023

8:30 AM Arrival and Coffee
Arrival and Coffee
8:30 AM - 9:15 AM
Room: Main Auditorium
9:15 AM Opening
Opening
9:15 AM - 10:30 AM
Room: Main Auditorium
Contributions

9:15 AM Welcome and Logistics

9:30 AM Experimental Introducton - Kevin Pedro (Fermi National Accelerator Lab. (US))

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

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

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

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

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

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

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

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

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

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

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

12:00 PM Towards Novel Charged Particle Tracking Approaches with Transformer and U-Net Models - Zef Wolffs (Nikhef National institute for subatomic physics (NL))
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
Room: Main Auditorium
2:00 PM
2:00 PM - 3:30 PM
Room: Seminarraum 4a/b
Contributions

2:00 PM Event Reconstruction with GNNs at the FCC - Dolores Garcia (CERN)

2:15 PM Time-of-Flight Estimation using Machine Learning Techniques - Konrad Helms

2:30 PM Set2Tree: Particle decay reconstruction via GNN - Dmitrii Kobylianskii (Weizmann Institute of Science (IL))

2:45 PM End-to-end analysis with jointly optimized particle identification and analysis optimization objectives - Matthias Vigl (Technische Universitat Munchen (DE))

3:00 PM 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)

3:15 PM Reconstructing ALP properties and optimizing experimental design with simulation-based inference - Alessandro Morandini
2:00 PM - 3:30 PM
Room: Main Auditorium
Contributions

2:00 PM Regression-based refinement of fast simulation - Moritz Jonas Wolf (Hamburg University (DE))

2:15 PM Refining Fast Calorimeter Simulations with a Schrödinger Bridge - Sascha Diefenbacher (Lawrence Berkeley National Lab. (US))

2:30 PM SuperCalo: Calorimeter shower super-resolution - Ian Pang

2:45 PM Denoising Graph Super-Resolution with Diffusion Models and Transformers for Improved Particle Reconstruction - Nilotpal Kakati (Weizmann Institute of Science (IL))

3:00 PM SR-GAN for SR-gamma: photon super resolution at collider experiments - Florian Alexander Mausolf (Rheinisch Westfaelische Tech. Hoch. (DE))
3:30 PM Coffee
Coffee
3:30 PM - 4:00 PM
Room: Main Auditorium
4:00 PM
4:00 PM - 6:15 PM
Room: Main Auditorium
Contributions

4:00 PM Generic representations of jets at detector-level with self supervised learning - Etienne Dreyer (Weizmann Institute of Science (IL))

4:15 PM CoCo: Contrastive Combinatorics - Debajyoti Sengupta (Universite de Geneve (CH))

4:30 PM Identifying semi-visible jets with darkCLR - Tanmoy Modak

4:45 PM Reconstructing full pp collision events with HGPflow - Nilotpal Kakati (Weizmann Institute of Science (IL))

5:30 PM Scalable neural network models and terascale datasets for particle-flow reconstruction - Joosep Pata (National Institute of Chemical Physics and Biophysics (EE))

5:45 PM Masked particle modelling - Matthew Leigh (University of Geneva)

6:00 PM ML-assisted reconstruction of hadron-collider events with mini-jets - Josef Modestus Murnauer (Max Planck Society (DE))
6:30 PM Reception
Reception
6:30 PM - 8:30 PM
Room: Kantine-Anbau
Tuesday, November 7, 2023
9:00 AM
9:00 AM - 10:30 AM
Room: Main Auditorium
Contributions

9:00 AM Deep learning methods for noise filtering in the NA61/SHINE experiment - Marcin Slodkowski (Warsaw University of Technology (PL))

9:15 AM The application of neural networks for the calibration of topological cell clusters in the ATLAS calorimeters - Peter Loch (University of Arizona (US))

9:30 AM Jets as sets or graphs: Fast jet classification on FPGAs for efficient triggering at the HL-LHC - Denis-Patrick Odagiu (ETH Zurich (CH))

9:45 AM 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 AM Realtime Anomaly Detection in the CMS Experiment Global Trigger Test Crate - Jannicke Pearkes (University of Colorado Boulder (US))

10:15 AM LLPNet: Graph Autoencoder for Triggering Light Long-Lived Particles at HL-LHC - Prabhat Solanki (Indian Institute of Science, Bengaluru)
9:00 AM - 9:45 AM
Room: Seminarraum 4a/b
Contributions

9:00 AM Learning a Representation of New Physics Models - Tore von Schwartz

9:15 AM Anatomy of Jet classification using deep learning - Sung Hak Lim (Rutgers University)

9:30 AM Hyperbolic Machine Learning for Jet Physics - Nathaniel Sherlock Woodward (Massachusetts Inst. of Technology (US))
10:30 AM Coffee
Coffee
10:30 AM - 11:00 AM
Room: Main Auditorium
11:00 AM
11:00 AM - 12:30 PM
Room: Main Auditorium
Contributions

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

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

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

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

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

12:15 PM DeepTreeGAN: Fast Generation of High Dimensional Point Clouds - Moritz Scham (Deutsches Elektronen-Synchrotron (DE))
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
Room: Main Auditorium
1:45 PM
1:45 PM - 3:30 PM
Room: Main Auditorium
Contributions

1:45 PM Conditional Set-to-Set Generation for Fast Simulation using Diffusion and Graph-to-Graph Translation - Nathalie Soybelman (Weizmann Institute of Science (IL))

2:00 PM CaloGraph: Calorimeter simulation via Graph-based diffusion model - Dmitrii Kobylianskii (Weizmann Institute of Science (IL))

2:15 PM High-Dimensional Diffusion Generative Models in Collider Physics - Vinicius Massami Mikuni (Lawrence Berkeley National Lab. (US))

2:30 PM CaloDiffusion with GLaM for High Fidelity Calorimeter Simulation - Kevin Pedro (Fermi National Accelerator Lab. (US))

2:45 PM Diffusion Models for the LHC - Sofia Palacios Schweitzer (ITP, University Heidelberg)

3:00 PM CaloClouds: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation - Erik Buhmann (Hamburg University (DE))

3:15 PM CaloLatent: Score-based Generative Modelling in the Latent Space for Calorimeter Shower Generation - Thandikire Madula (University College London)
2:00 PM
2:00 PM - 3:30 PM
Room: Seminarraum 4a/b
Contributions

2:00 PM Learning the language of QCD jets with transformers - Alexander Mück (RWTH Aachen University)

2:15 PM Off-Shell Processes from Neural Networks - Mathias Kuschick

2:30 PM High multiplicity with JetGPT - Jonas Spinner

2:45 PM Generate parton-level events from reconstructed events with Conditional Normalizing Flows - Davide Valsecchi (ETH Zurich (CH))

3:00 PM MEMeNNto – Matrix Element Method with Neural Networks - Nathan Huetsch (Institut für Theoretische Physik, Universität Heidelberg)

3:15 PM The MadNIS Reloaded - Theo Heimel (Heidelberg University)
3:30 PM Coffee
Coffee
3:30 PM - 4:00 PM
Room: Main Auditorium
4:00 PM
4:00 PM - 5:00 PM
Room: Main Auditorium
Contributions

4:00 PM Keynote: Physics ex machina - Machine learning for fundamental physics - David Shih
5:00 PM Brezels
Brezels
5:00 PM - 5:30 PM
Room: Main Auditorium

7:00 PM 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)
7:00 PM - 9:00 PM
Room: Main Auditorium
Wednesday, November 8, 2023
9:00 AM
9:00 AM - 10:30 AM
Room: Main Auditorium
Contributions

9:00 AM Machine Learning in Astrophysics and Astronomy - Caroline Heneka

9:30 AM Mapping Dark Matter in the Milky Way using Normalizing Flows and Gaia DR3 - Eric Putney (Rutgers, The State University of New Jersey)

9:45 AM Bayesian Insights into the high-redshift Universe with 21cmPIE-cINN - Benedikt Schosser (Heidelberg University) Theo Heimel (Heidelberg University)

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

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

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

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

11:30 AM Evaluating Equivariance for Reconstruction - Savannah Thais

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

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

12:15 PM - 12:30 PM
Room: Main Auditorium

12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
Room: Main Auditorium
2:00 PM
2:00 PM - 3:30 PM
Room: Main Auditorium
Contributions

2:00 PM ML for jets and beyond jets - Huilin Qu (CERN)

2:30 PM PELICAN Update: Equivariance, Explainability, and Robustness in Jet ML - Timothy Hoffman

2:45 PM Particle Transformer with built-in IRC safety - Congqiao Li (Peking University (CN))

3:00 PM Combining Energy Correlators with Machine Learning - Katherine Fraser (Harvard University)

3:15 PM SPECTER: Efficient Evaluation of the Spectral EMD - Rikab Gambhir (MIT)
3:30 PM Coffee
Coffee
3:30 PM - 4:00 PM
Room: Main Auditorium
4:00 PM
4:00 PM - 5:45 PM
Room: Seminarraum 4a/b
Contributions

4:00 PM Back to the Roots: Tree-Based Algorithms for Weakly Supervised Anomaly Detection - Marie Hein (RWTH Aachen University)

4:15 PM Robust Anomaly Detection in the Presence of Irrelevant Features - Yik Chuen San

4:30 PM Drapes: Diffusion for weak supervision - Matthew Leigh (University of Geneva)

4:45 PM The Interplay of Machine Learning–based Resonant Anomaly Detection Methods - Radha Mastandrea (University of California, Berkeley)

5:00 PM Full Phase Space Resonant Anomaly Detection - Cedric Ewen

5:15 PM Combining resonant and tail-based anomaly detection - Gerrit Bickendorf (Universität Bonn)
4:00 PM - 5:30 PM
Room: Main Auditorium
Contributions

4:00 PM Classifying the CP properties of the ggH coupling in H+2j production - Henning Bahl

4:15 PM Returning CP-Observables to the Frames they Belong - Jona Ackerschott

4:30 PM End-To-End Latent Variational Diffusion Models for Unfolding LHC Events - Kevin Thomas Greif (University of California Irvine (US))

4:45 PM Deep learning assisted unbinned measurements of jet substructure observables with the H1 detector - Vinicius Massami Mikuni (Lawrence Berkeley National Lab. (US))

5:00 PM Exploring the universality of jet quenching via Bayesian inference - Alexandre Falcão (University of Bergen)

5:15 PM Apples to Apples in Jet Quenching - João A. Gonçalves (LIP - Lisbon / IST - Universidade de Lisboa)
Thursday, November 9, 2023
9:00 AM
9:00 AM - 10:00 AM
Room: Main Auditorium
Contributions

9:00 AM Non-resonant Anomaly Detection with Background Extrapolation - Kehang Bai (University of Oregon (US))

9:15 AM R-ANODE - Ranit Das (Rutgers University)

9:30 AM Anomaly Detection in Collider Physics via Factorized Observables - Raymond Wynne (MIT)

9:45 AM Unsupervised tagging of semivisible jets with normalized autoencoders in CMS - Florian Eble (ETH Zurich (CH))
10:00 AM
10:00 AM - 10:30 AM
Room: Main Auditorium
Contributions

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

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

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

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

11:45 AM 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 PM The Fast Calorimeter Simulation Challenge 2022 - Claudius Krause (Rutgers University)
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
Room: Main Auditorium
2:00 PM
2:00 PM - 3:45 PM
Room: Main Auditorium
Contributions

2:00 PM The DL Advocate: Playing the devil's advocate with hidden systematic uncertainties - Andrea Mauri (Imperial College (GB))

2:15 PM Systematic Effects in Jet Tagging Performance for the ATLAS Detector - Kevin Thomas Greif (University of California Irvine (US))

2:30 PM Evaluating Neural Network Uncertainty Estimation with Inconsistent Training Data - Giovanni De Crescenzo

2:45 PM Generalization Properties of Jet Classification - Sebastian Guido Bieringer (Hamburg University)

3:00 PM Deciphering the Structure of EFTs from String Theory using JAX and Reinforcement Learning - Andreas Schachner (Ludwig-Maximilians-Universität München)

3:15 PM Towards a phenomenological understanding of neural networks - Samuel Tovey (University of Stuttgart)

3:30 PM Machine Learning to Understand String Theory EFTs - Sven Krippendorf (LMU Munich)
3:45 PM Coffee
Coffee
3:45 PM - 4:15 PM
Room: Main Auditorium
4:15 PM
4:15 PM - 5:00 PM
Room: Main Auditorium
Contributions

4:15 PM Cluster Scanning - Ivan Oleksiyuk (UNIGE)

4:30 PM Anomaly Detection in High Energy Physics via Non-Gaussian Variational Autoencoders - Thomas Dartnall Stern (University of Cape Town (ZA))

4:45 PM Quantum anomaly detection in the latent space of proton collision events at the LHC - Vasilis Belis (ETH Zurich (CH))
5:20 PM
5:20 PM - 6:00 PM
Contributions

5:20 PM Binary Discrimination at Next-to-Leading Order - Andrew Larkoski (UCLA)

5:25 PM Scalar Field Theories via Neural Networks at Initialization - Anindita Maiti (Perimeter Institute for Theoretical Physics)

5:30 PM Learning Broken Symmetries with Encouraged Invariance - Daniel Whiteson (University of California Irvine (US)) Edmund Witkowski (UCI)

5:35 PM 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)

5:40 PM Perturbatively Regularized Neural Networks - Chase Owen Shimmin (Yale University (US))
Friday, November 10, 2023
9:00 AM
9:00 AM - 10:30 AM
Room: Main Auditorium
Contributions

9:00 AM Giving events a new shape : measurements of multijet event isotropy at ATLAS using optimal transport - Matt LeBlanc (University of Manchester (GB))

9:15 AM Sensitivity Studies for Search of B+ → K∗+ νν using Lorentz Equivariant Neural Networks at the Belle II Experiment - Caspar Schmitt

9:30 AM 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))

9:45 AM Jet formation with Chebyshev Polynomials - Henry Day-Hall (Czech Technical University in Prague (CZ))

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

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

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

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

11:35 AM Announcement of ML4Jets 2024

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