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08:45
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--- Registration ---
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09:30
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Welcome
- Prof.
Maria Spiropulu
(California Institute of Technology)
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09:40
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Invited Plenaries
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Jennifer Ngadiuba
(FNAL)
(until 11:00)
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09:40
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AI for gravitational waves
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Philip Coleman Harris
(Massachusetts Inst. of Technology (US))
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10:20
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End-to-end particle reconstruction for current and future colliders
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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
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Maurizio Pierini
(CERN)
(until 12:50)
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11:30
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Progress on AI-based jet tagging
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Javier Mauricio Duarte
(Univ. of California San Diego (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
-Dr
Jean-Roch Vlimant
(California Institute of Technology (US))
(until 10:20)
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09:00
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AI for particle accelerators [Remote]
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Auralee Edelen
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09:40
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Foundation models for astrophysics & cosmology [Remote]
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Gautham Narayan
(University of Illinois at Urbana-Champaign / SkAI Institute)
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10:20
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--- Coffee break ---
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10:50
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Anomaly Detection
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Benedikt Maier
(Imperial College (GB))
(until 12:50)
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10:50
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Anomaly detections in 3 lepton channel using AutoEncoders
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Alfredo Castaneda
(Universidad de Sonora (MX))
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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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Oz Amram
(Fermi National Accelerator Lab. (US))
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11:50
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Weakly supervised anomaly detection with event-level variables
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Liam Brennan
(Univ. of California Santa Barbara (US))
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12:10
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Improving the model agnostic sensitivity of weakly supervised anomaly detection
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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
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Melissa Quinnan
(Univ. of California San Diego (US))
(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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Noah Clarke Hall
(University College London)
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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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Abhijith Gandrakota
(Fermi National Accelerator Lab. (US))
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11:30
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DECADE: Selecting the unexpected with decorrelated anomaly triggers
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Noah Clarke Hall
(University College London)
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11:50
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It's not a FAD: how to use Flows for Anomaly Detection on FPGAs
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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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Fotis Giasemis
(Centre National de la Recherche Scientifique (FR))
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12:30
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Jet calibration with in-situ pileup suppression for the L1 trigger
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Ben Carlson
(Westmont College)
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09:00
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Invited Plenaries
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Abhijith Gandrakota
(Fermi National Accelerator Lab. (US))
(until 10:20)
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09:00
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Likelihood free inference
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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
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Oz Amram
(Fermi National Accelerator Lab. (US))
(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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Radha Mastandrea
(LBNL)
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11:30
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Incorporating Physical Priors into Weakly-Supervised Anomaly Detection
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Gurpreet Singh
(University of California, Berkeley)
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11:50
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Anomaly Detection applied to the Quality Control of new detector components
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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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Denis-Patrick Odagiu
Denis-Patrick Odagiu
(ETH Zurich (CH))
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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
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Vinicius Massami Mikuni
(Lawrence Berkeley National Lab. (US))
(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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Melissa Quinnan
(Univ. of California San Diego (US))
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11:10
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Fast and Precise Track Fitting with Machine Learning
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Daniel Whiteson
(University of California Irvine (US))
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11:30
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MaskFormers for Reconstruction Tasks in High Energy Physics
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Max Hart
(University College London (GB))
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11:50
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A Graph Neural Network Approach for General Reconstruction of Non-Helical Tracks [remote]
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Levi Condren
(University of California Irvine (US))
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12:10
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Machine Learning for Dark Matter searches at the LHC
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Rafal Maselek
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12:30
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$\texttt{DeepSub}$: Deep Learning for Thermal Background Subtraction in Heavy-Ion Collisions [remote]
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Umar Sohail Qureshi
(Vanderbilt University)
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09:30
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Invited Plenaries
-
David Shih
(until 10:50)
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09:30
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AI-based end-to-end simulation
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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
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Raghav Kansal
(Caltech / Fermilab)
(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
- Mr
Jhoao Gabriel Martins Campos Almeida Arneiro
(Universidade de Sao Paulo (USP) (BR))
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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 [Remote]
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Jai Bardhan
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12:00
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Jet tagging with the Lund Jet Plane
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Ethan Lewis Simpson
(The University of Manchester (GB))
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12:20
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[Remote] Integrating Energy Flow Networks with Jet Substructure Observables for Enhanced Jet Quenching Studies
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João A. Gonçalves
(LIP - IST)
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12:40
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Comparing Continuous and Tokenized Jet Generation Approaches for Precision Modeling
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Ian Pang
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11:20
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Theory
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Rikab Gambhir
(MIT)
(until 12:40)
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11:20
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Autonomous Model Building with Reinforcement Learning: An Application with Lepton Flavor Symmetries
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Jake Rudolph
(UC Irvine)
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11:40
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Observable Optimization for Precision Theory: Machine Learning Energy Correlators
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Katherine Fraser
(Harvard University)
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12:00
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Giving machine learning a boost towards respecting (approximate) symmetries
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Inbar Savoray
(UC Berkeley)
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12:20
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An Energy Correlation Function tagger for gluon-gluon resonances
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Connor Moore
(University of Notre Dame (US))
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09:00
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Reconstruction and Analysis
-Dr
Claudius Krause
(HEPHY Vienna (ÖAW))
(until 10:40)
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09:20
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Boosting HH(4b) beyond boosted HH(4b): a calibratable full-particle search framework
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Tianyi Yang
(Peking University (CN))
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09:40
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Going HyPER: Enhancing collider measurements with hypergraph learning
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Ethan Lewis Simpson
(The University of Manchester (GB))
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10:00
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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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Vinicius Massami Mikuni
(Lawrence Berkeley National Lab. (US))
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10:20
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Optimal Transport for $e/\pi^0$ Particle Classification in LArTPC Neutrino Experiments
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Jessica N. Howard
(Kavli Institute for Theoretical Physics)
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09:00
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Theory
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Prasanth Shyamsundar
(Fermi National Accelerator Laboratory)
(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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Tanvi Wamorkar
(Lawrence Berkeley National Lab. (US))
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09:20
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Machine Learning Neutrino-Nucleus Cross Sections [remote]
- Dr
Karla Tame-Narvaez
(Fermilab National Accelerator Laboratory)
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09:40
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A novel loss function to optimise signal significance in particle physics [remote]
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Jai Bardhan
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10:00
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Machine Learning Symmetries in Physics from First Principles
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Konstantin Matchev
(University of Alabama (US))
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10:20
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Quantum
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Prasanth Shyamsundar
(Fermi National Accelerator Laboratory)
(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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Benedikt Maier
(Imperial College (GB))
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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 [remote]
- 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
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Jennifer Ngadiuba
(FNAL)
(until 12:10)
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11:30
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AI for Mathematics
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Ali Shehper
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16:30
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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
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Andrea Rizzi
(Universita & INFN Pisa (IT))
(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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Raymundo Ramos
(Korea Institute for Advanced Study)
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14:20
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Stay Positive: Neural Refinement of Simulated Event Weights
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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
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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
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Francesco Vaselli
(Scuola Normale Superiore & INFN Pisa (IT))
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14:00
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Jet Physics
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Philip Coleman Harris
(Massachusetts Inst. of Technology (US))
(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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Leonardo Lima Da Silva
(Universidade de Sao Paulo (USP) (BR))
Marcelo Gameiro Munhoz
(Universidade de Sao Paulo (USP) (BR))
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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
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Zichun Hao
(California Institute of Technology)
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15:00
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Particle transformers for boosted H→WW identification
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Raghav Kansal
(Caltech / Fermilab)
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15:20
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--- Coffee break ---
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15:50
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Summary of Day; Q&A
(until 16:30)
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15:50
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Monday Summary
- Dr
Jean-Roch Vlimant
(California Institute of Technology (US))
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16:30
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Keynote
(until 17:30)
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16:30
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Anima Anandkumar (Caltech)
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12:50
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--- Lunch break ---
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14:00
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Jet Physics
-
Raghav Kansal
(Caltech / Fermilab)
(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
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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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Diptaparna Biswas
(Universitaet Siegen (DE))
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15:00
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Blooming LHC analyses with all-inclusive pretrained boosted-jet models
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Dawei Fu
(Peking University (CN))
Congqiao Li
(Peking University (CN))
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14:00
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Uncertainties & Interpretability
-Prof.
Mariel Pettee
(University of Wisconsin--Madison)
(until 15:20)
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14:00
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Physics-guided Machine Learning in Cosmology [remote]
-
Leonora KARDUM
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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
-
Po-Wen Chang
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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 [remote]
-
Jai Bardhan
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15:20
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--- Coffee break ---
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15:50
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Summary of Day; Q&A
(until 16:30)
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15:50
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Tuesday Summary
-
Benedikt Maier
(Imperial College (GB))
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16:30
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Keynote
(until 17:30)
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16:30
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Stefano Soatto (AWS AI)
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12:50
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--- Lunch break ---
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14:00
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Jet Physics
-
Daniel Whiteson
(University of California Irvine (US))
(until 15:20)
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14:00
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Transformer-based tagger for boosted Higgs
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Edoardo Critelli
(UCL (GB))
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14:20
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Fragmentation tagging
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Yevgeny Kats
(Ben-Gurion University)
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14:40
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The Pareto Frontier of Resilient Jet Tagging
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Rikab Gambhir
(MIT)
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15:00
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Fast Jet Tagging with MLP-Mixers on FPGAs
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Chang Sun
(California Institute of Technology (US))
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14:00
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Unfolding & Inference
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Eilam Gross
(Weizmann Institute of Science (IL))
(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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Oz Amram
(Fermi National Accelerator Lab. (US))
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14:20
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A High-Dimensional, Unbinned Standard Model Measurement with the ATLAS Experiment
-
Mariel Pettee
(Lawrence Berkeley National Lab. (US))
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14:40
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Higgs Signal Strength Estimation with a Dual-Branch GNN under Systematic Uncertainties [remote]
-
Daohan Wang
(HEPHY ÖAW)
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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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Keynote
(until 16:50)
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15:50
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Katie Bouman (Caltech)
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16:50
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--- Group photo ---
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18:00
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--- ML4JETS BANQUET ---
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13:00
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--- Lunch break ---
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14:10
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Fast ML
-
Jannicke Pearkes
(University of Colorado Boulder (US))
(until 15:30)
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14:10
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Spatially Aware Linear Transformer (SAL-T) for Efficient Particle Jet Identification
-
Aaron Wang
(University of Illinois Chicago (US))
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14:30
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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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14:50
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GELATO: A Generic Event-Level Anomalous Trigger Option for ATLAS
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Sagar Addepalli
(SLAC National Accelerator Laboratory (US))
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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)
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14:10
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Unfolding & Inference
-
Aishik Ghosh
(University of California Irvine (US))
(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
-
Sascha Diefenbacher
(Lawrence Berkeley National Lab. (US))
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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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Keynote
(until 17:00)
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16:00
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Jeff Nessen (Google AI)
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17:00
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Summary of Day; Q&A
-
David Shih
(until 17:30)
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17:00
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Thursday Summary
-
David Shih
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12:10
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Summary & Highlights
-
Andrea Rizzi
(Universita & INFN Pisa (IT))
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12:30
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Closing remarks
-
Jennifer Ngadiuba
(FNAL)
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