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09:00
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--- Registration ---
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09:40
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Invited Plenaries
(until 11:00)
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09:40
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Progresses on AI-based jet tagging
-
Huilin Qu
(CERN)
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10:20
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End-to-end particle reconstruction for current and future colliders
-
Eilam Gross
(Weizmann Institute of Science (IL))
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11:00
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--- Coffee break ---
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11:30
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Invited Plenaries
(until 12:50)
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11:30
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AI for gravitational waves
-
Philip Coleman Harris
(Massachusetts Inst. of Technology (US))
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12:10
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Uncertainty quantification in machine learning: A selective overview
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Prasanth Shyamsundar
(Fermi National Accelerator Laboratory)
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09:00
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Invited Plenaries
(until 10:20)
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09:00
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AI for particle accelerators
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Auralee Edelen
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09:40
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Foundation models for astrophysics & cosmology
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Gautham Narayan
(SkAI)
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10:20
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--- Coffee break ---
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10:50
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Anomaly Detection
(until 12:50)
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10:50
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Anomaly detections in 3 lepton channel using AutoEncoders #35
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11:10
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Event-level Observables based on Optimal Transport for Resonant Anomaly Detection
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Aditya Bhargava
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11:30
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Anomaly Detection Results from CMS
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CMS Collaboration
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11:50
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Weakly supervised anomaly detection with event-level variables
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12:10
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Improving the model agnostic sensitivity of weakly supervised anomaly detection
-
Marie Hein
(RWTH Aachen University)
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12:30
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Testing the Robustness of Via Machinae Stellar Stream Detections Using Resonant Anomaly Detection
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Rafael Porto
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10:50
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Fast ML
(until 12:50)
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10:50
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Convolutional Neural Networks for pile-up suppression in the ATLAS Global Trigger
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11:10
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Towards a Self-Driving Trigger: Adaptive Response to Anomalies in Real Time
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11:30
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DECADE: Selecting the unexpected with decorrelated anomaly triggers
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11:50
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It's not a FAD: how to use Flows for Anomaly Detection on FPGAs
-
Francesco Vaselli
(Scuola Normale Superiore & INFN Pisa (IT))
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12:10
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Comparative Analysis of FPGA and GPU Performance for Machine Learning-Based Track Reconstruction at LHCb
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12:30
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Real-Time event reconstruction for Nuclear Physics Experiments using Artificial Intelligence
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Gagik Gavalian
(Jefferson National Lab)
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09:00
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Invited Plenaries
(until 10:20)
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09:00
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Likelihood free inference
-
Aishik Ghosh
(University of California Irvine (US))
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09:40
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AI-driven detector design
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Shah Rukh Qasim
(University of Zurich (CH))
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10:20
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--- Coffee break ---
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10:50
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Anomaly Detection
(until 12:50)
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10:50
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Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data
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11:10
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A Novel Anomaly Detection Approach for Primary Vertex Selection at the HL-LHC
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Wasikul Islam
(University of Wisconsin-Madison (US))
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11:30
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Incorporating Physical Priors into Weakly-Supervised Anomaly Detection
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11:50
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Anomaly Detection applied to the Quality Control of new detector components
-
Louis Vaslin
(KEK High Energy Accelerator Research Organization (JP))
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12:10
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Debiasing Ultrafast Anomaly Detection with Posterior Agreement
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12:30
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Anomaly Detection in High-Energy Particle Collisions at the LHC
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Runze Li
(Yale University (US))
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10:50
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Reconstruction and Analysis
(until 12:50)
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10:50
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Neural autoregressive flows for data-driven background estimation in a search for four-top quark production in the all-hadronic final state with CMS at 13 TeV
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11:10
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A Graph Neural Network Approach for General Reconstruction of Non-Helical Tracks
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11:30
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MaskFormers for Reconstruction Tasks in High Energy Physics
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11:50
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Fast and Precise Track Fitting with Machine Learning
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12:10
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Machine Learning for Dark Matter searches at the LHC
-
Rafal Maselek
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12:30
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$\texttt{DeepSub}$: Deep Learning for Thermal Background Subtraction in Heavy-Ion Collisions
-
Umar Sohail Qureshi
(Vanderbilt University)
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09:30
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Invited Plenaries
(until 10:50)
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09:30
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AI-based end-to-end simulation
-
Andrea Rizzi
(Universita & INFN Pisa (IT))
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10:10
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AI at the extreme edge
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Jannicke Pearkes
(University of Colorado Boulder (US))
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10:50
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--- Coffee break ---
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11:20
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Jet Physics
(until 13:00)
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11:20
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Deep Learning Methods for Jet Tagging and Process Classification Using Image Processing
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11:40
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HEP-JEPA: Towards a found model for high energy physics using joint embedding predictive architecture
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12:00
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Jet tagging with the Lund Jet Plane
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12:20
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Fast Jet Tagging with MLP-Mixers on FPGAs
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12:40
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Comparing Continuous and Tokenized Jet Generation Approaches for Precision Modeling
-
Ian Pang
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11:20
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Theory
(until 13:00)
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11:20
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Multi-scale Optimal Transport for Complete Collider Events
-
Lynn Lin
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11:40
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Autonomous Model Building with Reinforcement Learning: An Application with Lepton Flavor Symmetries
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12:00
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Observable Optimization for Precision Theory: Machine Learning Energy Correlators
-
Katherine Fraser
(Harvard University)
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12:20
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Giving machine learning a boost towards respecting (approximate) symmetries
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12:40
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An Energy Correlation Function tagger for gluon-gluon resonances
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09:00
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Reconstruction and Analysis
(until 11:00)
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09:00
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Search for keV-scale Sterile Neutrinos with TRISTAN at KATRIN Using a Neural Network-Based Approach
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09:20
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Simultaneous reconstruction of boosted, resolved, and semi-boosted top-quark events with symmetry-preserving attention networks
-
Thomas Coulter Sievert
(California Institute of Technology (US))
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09:40
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Boosting HH(4b) beyond boosted HH(4b): a calibratable full-particle search framework
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10:00
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Going HyPER: Enhancing collider measurements with hypergraph learning
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10:20
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Machine Learning-Assisted Measurement of Lepton-Jet Azimuthal Angular Asymmetries and of the complete final state in Deep-Inelastic Scattering at HERA
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10:40
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Optimal Transport for $e/\pi^0$ Particle Classification in LArTPC Neutrino Experiments
-
Jessica N. Howard
(Kavli Institute for Theoretical Physics)
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09:00
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Theory
(until 10:20)
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09:00
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Explicit versus implicit physics priors for separating nearly identical classes
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09:20
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Machine Learning Neutrino-Nucleus Cross Sections
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09:40
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A novel loss function to optimise signal significance in particle physics
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10:00
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Machine Learning Symmetries in Physics from First Principles
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10:20
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Quantum
(until 11:00)
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10:20
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1 Particle - 1 Qubit: Particle Physics Data Encoding for Quantum Machine Learning
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10:40
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Quantum-Enhanced Inference for Four-Top-Quark Signal Classification at the LHC Using Graph Neural Networks
- Mr
Syed Haider Ali
(Department of Physics & Applied Mathematics, Pakistan Institute of Engineering and Applied Sciences (PIEAS), P. O. Nilore 45650, Islamabad)
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11:00
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--- Coffee break ---
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11:30
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Invited Plenaries
(until 12:10)
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11:30
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AI in HEP Theory
-
Ali Shehper
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17:30
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--- Welcome reception ---
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12:50
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--- Lunch break ---
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14:00
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Event Generation and Detector Simulation
(until 15:20)
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14:00
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DLScanner and LeStrat-Net: Machine learning for improved Monte Carlo exploration
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14:20
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Stay Positive: Neural Refinement of Simulated Event Weights
-
Dennis Daniel Nick Noll
(Lawrence Berkeley National Lab (US))
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14:40
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EveNet: Towards a Generalist Event Transformer for Unified Understanding and Generation of Collider Data
-
Yulei Zhang
(University of Washington (US))
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15:00
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CMS FlashSim: an end-to-end ML approach speeds up simulation in CMS
-
CMS Collaboration
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14:00
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Jet Physics
(until 15:20)
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14:00
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Machine Learning Approaches for Investigating Jet Quenching in Quark-Gluon Plasma via Jet Substructures Analysis
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14:20
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IAFormer: Interaction-Aware Transformer network for collider data analysis
- Dr
Ahmed Hammad
(KEK, Japan)
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14:40
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Representation Learning of Jets with Physics-Informed Self-Distillations
-
Zichun Hao
(California Institute of Technology)
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15:00
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Particle transformers for boosted H→WW identification
-
CMS Collaboration
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15:20
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--- Coffee break ---
|
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15:50
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Day Summary & Q/A
(until 16:30)
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15:50
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--- Coffee break ---
|
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16:30
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Keynote
(until 17:30)
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|
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12:50
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--- Lunch break ---
|
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14:00
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Jet Physics
(until 15:20)
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14:00
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Get Your Jets in Shape: Conditioning Heads and Backbones
-
Ian Pang
|
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14:20
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A comparison of self-supervised pre-training methods for foundation models in jet physics
-
Joschka Birk
(Hamburg University (DE))
|
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14:40
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Heavy-Flavour Frontier: Tagging at ATLAS with GN3
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15:00
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Blooming LHC analyses with all-inclusive pretrained boosted-jet models
-
Congqiao Li
(Peking University (CN))
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14:00
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Uncertainties & Interpretability
(until 15:20)
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14:00
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Physics-guided Machine Learning in Cosmology
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14:20
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Fair Universe HiggsML Uncertainty Challenge: Benchmark for Uncertainty-Aware Machine Learning in High Energy Physics
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14:40
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Unbinned inclusive cross-section measurements with machine-learned systematic uncertainties
- Dr
Claudius Krause
(HEPHY Vienna (ÖAW))
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15:00
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Tackling interpretability with physical baselines for Integrated Gradients
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15:20
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--- Coffee break ---
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15:50
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Day Summary & Q/A
(until 16:30)
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16:30
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Keynote
(until 17:30)
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|
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12:50
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--- Lunch break ---
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14:00
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Jet Physics
(until 15:20)
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14:00
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Transformer-based tagger for boosted Higgs
|
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14:20
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Fragmentation tagging
-
Yevgeny Kats
(Ben-Gurion University)
|
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14:40
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The Pareto Frontier of Resilient Jet Tagging
-
Rikab Gambhir
(MIT)
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15:00
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Integrating Energy Flow Networks with Jet Substructure Observables for Enhanced Jet Quenching Studies
-
João A. Gonçalves
(LIP - IST)
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14:00
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Unfolding & Inference
(until 15:20)
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14:00
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Data-Driven High Dimensional Statistical Inference with Generative Models
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14:20
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A High-Dimensional, Unbinned Standard Model Measurement with the ATLAS Experiment
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14:40
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Higgs Signal Strength Estimation with a Dual-Branch GNN under Systematic Uncertainties
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15:00
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wifi Ensembles for Simulation-Based Inference with Systematic Uncertainties
-
Sean Benevedes
(Massachusetts Institute of Technology)
|
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15:20
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--- Coffee break ---
|
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15:50
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Day Summary & Q/A
(until 16:30)
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18:00
|
--- Social dinner ---
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13:00
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--- Lunch break ---
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14:10
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Fast ML
(until 15:30)
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14:10
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Efficient Transformers for Jet Tagging
|
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14:30
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Jet calibration with in-stiu pileu suppression for the L1 trigger
-
Ben Carlson
(Westmont College)
|
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14:50
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GELATO: A Generic Event-Level Anomalous Trigger Option for ATLAS
|
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15:10
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Real-Time Compression of CMS Detector Data Using Conditional Autoencoders
-
Zachary Baldwin
(Carnegie Mellon University)
|
|
14:10
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Unfolding & Inference
(until 15:30)
|
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14:10
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Forward folding versus unfolding in the age of ML
-
Kevin Thomas Greif
(University of California Irvine (US))
|
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14:30
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Discriminative versus Generative Approaches to Simulation-based Inference
|
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14:50
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On focusing statistical power for searches and measurements in particle physics
-
James Carzon
(Carnegie Mellon University)
|
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15:10
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Generator Based Inference (GBI)
-
Alkaid Cheng
(University of Wisconsin Madison (US))
|
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15:30
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--- Coffee break ---
|
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16:00
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Day Summary & Q/A
(until 16:40)
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