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10:00 AM
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Plenary
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Pietro Vischia
(Universite Catholique de Louvain (UCL) (BE))
(until 12:00 PM)
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10:00 AM
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Introduction
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Gian Michele Innocenti
(CERN)
David Rousseau
(LAL-Orsay, FR)
Lorenzo Moneta
(CERN)
Andrea Wulzer
(CERN and EPFL)
Riccardo Torre
(CERN)
Simon Akar
(University of Cincinnati (US)) Dr
Pietro Vischia
(Universite Catholique de Louvain (UCL) (BE))
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10:15 AM
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CERN Knowledge Transfer
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Han Hubert Dols
(CERN)
Nick Ziogas
(CERN)
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10:25 AM
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Machine Learning in Procter and Gamble
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Michele Floris
(University of Derby (GB))
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10:55 AM
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Using Topological Data Analysis to Disentangle Complex Data Sets
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Maurizio Sanarico
(SDG Group)
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11:25 AM
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Zenseact : Deep learning and computer vision for self-driving cars
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Christoffer Petersson
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10:00 AM
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Workshop
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David Rousseau
(LAL-Orsay, FR)
Pietro Vischia
(Universite Catholique de Louvain (UCL) (BE))
(until 12:55 PM)
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10:00 AM
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GANplifying Event Samples
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Sascha Daniel Diefenbacher
(Hamburg University (DE))
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10:20 AM
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Generative models for calorimeters response simulation - from GANs through VAE to e2e SAE
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Kamil Rafal Deja
(Warsaw University of Technology (PL))
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10:40 AM
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Reduced Precision Strategies for Deep Learning: 3DGAN Use Case
- Mr
Florian Rehm
(Hochschule Coburg (DE))
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11:00 AM
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FastCaloGAN: a tool for fast simulation of the ATLAS calorimeter system with Generative Adversarial Networks
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Michele Faucci Giannelli
(INFN e Universita Roma Tor Vergata (IT))
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11:05 AM
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Estimating Support Size of Distribution Learnt by Generative Adversarial Networks for Particle Detector Simulation
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Kristina Jaruskova
(Czech Technical University in Prague)
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11:10 AM
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Fast simulation of Time Projection Chamber response at MPD using GANs
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Artem Maevskiy
(National Research University Higher School of Economics (RU))
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11:15 AM
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Domain Adaptation Techniques in Particle Identification for the ALICE experiment
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Michal Kurzynka
(Warsaw University of Technology (PL))
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11:20 AM
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Black-Box Optimization with Local Generative Surrogates
- Mr
Vladislav Belavin
(Yandex School of Data Analysis (RU))
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11:40 AM
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Using Machine Learning to Speed Up and Improve Detector R&D
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Alexey Boldyrev
(NRU Higher School of Economics (Moscow, Russia))
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12:00 PM
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Matrix Element Regression with Deep Neural Networks -- breaking the CPU barrier
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Florian Bury
(UCLouvain - CP3)
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12:20 PM
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Adaptive divergence for rapid adversarial optimization & (1 + epsilon)-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets
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Maxim Borisyak
(Yandex School of Data Analysis (RU))
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9:00 AM
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Workshop
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Lorenzo Moneta
(CERN)
(until 12:25 PM)
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9:00 AM
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AutoDQM: A Statistical Tool for Monitoring Data Quality in the CMS Detector
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Vivan Thi Nguyen
(Northeastern University (US))
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9:20 AM
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Quantum Graph Neural Networks for Track Reconstruction in Particle Physics and Beyond
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Cenk Tuysuz
(Middle East Technical University (TR))
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9:40 AM
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Quantum Generative Adversarial Networks
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Su Yeon Chang
(EPFL - Ecole Polytechnique Federale Lausanne (CH))
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10:00 AM
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--- Coffee Break ---
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10:20 AM
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SWAN: Powering CERN's Data Analytics and Machine Learning Use cases
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Prasanth Kothuri
(CERN)
Riccardo Castellotti
(CERN)
Luca Canali
(CERN)
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10:40 AM
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Accelerating GAN training using distributed tensorflow and highly parallel hardware
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Renato Paulo Da Costa Cardoso
(Universidade de Lisboa (PT))
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11:00 AM
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Using an Optical Processing Unit for tracking and calorimetry at the LHC
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David Rousseau
(IJCLab-Orsay)
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11:20 AM
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MLaaS4HEP: Machine Learning as a Service for HEP
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Luca Giommi
(Universita e INFN, Bologna (IT))
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11:25 AM
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Distributed training of graph neural network at HPC
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Xiangyang Ju
(Lawrence Berkeley National Lab. (US))
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11:30 AM
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Hyperparameter Optimisation for Machine Learning using ATLAS Grid and HPC
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Rui Zhang
(University of Wisconsin Madison (US))
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11:35 AM
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Identifying jets in the Lund plane
- Dr
Frederic Alexandre Dreyer
(University of Oxford)
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11:55 AM
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General recipe to form input space for deep learning analysis of HEP scattering processes.
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Lev Dudko
(M.V. Lomonosov Moscow State University (RU))
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10:00 AM
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Workshop
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Andrea Wulzer
(CERN and EPFL)
(until 12:20 PM)
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10:00 AM
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Foundations of a Fast, Data-Driven, Machine-Learned Simulator
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Jessica Nicole Howard
(University of California Irvine (US))
Jessica N. Howard
(Department of Physics & Astronomy, UC Irvine)
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10:20 AM
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Selective background MC simulation with graph neural networks at Belle II
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Nikolai Hartmann
(Ludwig Maximilians Universitat (DE))
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10:25 AM
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Pixel Detector Background Generation using Generative Adversarial Networks at Belle II
- Mr
Hosein Hashemi
(LMU)
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10:30 AM
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Reinforcement learning environment for deep learn physics dataset
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Maciej Witold Majewski
(AGH University of Science and Technology (PL)) Mr
Maciej Majewski
(AGH-UST)
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10:35 AM
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Improving particle-flow with deep learning
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Sanmay Ganguly
(Weizmann Institute of Science (IL))
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10:55 AM
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Super-resolution for calorimetry
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Francesco Armando Di Bello
(Sapienza Universita e INFN, Roma I (IT))
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11:15 AM
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Deep learning solutions for 2D calorimetric cluster reconstruction at LHCb
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Michal Mazurek
(National Centre for Nuclear Research (PL))
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11:35 AM
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Object condensation: one-stage grid-free multi-object reconstruction in physics detectors, graph, and image data
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Jan Kieseler
(CERN)
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11:55 AM
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UCluster: Unsupervised clustering for HEP
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Vinicius Massami Mikuni
(Universitaet Zuerich (CH))
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12:00 PM
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A readily-interpretable fully-convolutional autoencoder-like algorithm for unlabelled waveform analysis
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Benjamin Krikler
(University of Bristol (GB))
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2:00 PM
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HLS4ML tutorial
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Sioni Paris Summers
(CERN)
(until 5:00 PM)
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2:00 PM
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Plenary
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David Rousseau
(LAL-Orsay, FR)
(until 2:45 PM)
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2:00 PM
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Solving Inverse Problems with Invertible Neural Networks
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Ullrich Koethe
(Visual Learning Lab Heidelberg)
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3:00 PM
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Data Science Seminar
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Lorenzo Moneta
(CERN)
(until 4:00 PM)
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3:00 PM
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Structured models of objects, relations, and physics
- Dr
Peter Battaglia
(DeepMind)
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4:00 PM
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Plenary
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David Rousseau
(LAL-Orsay, FR)
(until 6:00 PM)
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4:00 PM
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Deep Learning @ LHC: An ATLAS Perspective
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Amir Farbin
(University of Texas at Arlington (US))
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4:45 PM
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End-to-End, Machine Learning-based Data Reconstruction for Particle Imaging Neutrino Detectors
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kazuhiro terao
(Stanford University)
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2:00 PM
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Workshop
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Gian Michele Innocenti
(CERN)
Simon Akar
(University of Cincinnati (US))
(until 5:00 PM)
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2:00 PM
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Accelerated pixel detector tracklet finding with Graph Neural Networks on FPGAs
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Savannah Jennifer Thais
(Princeton University (US))
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2:20 PM
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Set2Graph: Secondary Vertex finding in Jets with Neural Networks
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Jonathan Shlomi
(Weizmann Institute of Science (IL))
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2:40 PM
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Invertible Networks or Partons to Detector and Back Again
-
Anja Butter
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3:00 PM
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Hit-reco: ProtoDUNE denoising with DL models
-
Marco Rossi
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3:20 PM
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Efficiency parametrization with Neural Networks
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Nilotpal Kakati
(Weizmann Institute of Science (IL))
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3:40 PM
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--- Coffee Break ---
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4:10 PM
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Zero-Permutation Jet Parton Assignment
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Seungjin Yang
(University of Seoul, Department of Physics (KR))
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4:30 PM
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Design by intelligent committee: use of machine learning as a scientific advisor
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Stephen Burns Menary
(University of Manchester)
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5:00 PM
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Plenary
-
Simon Akar
(University of Cincinnati (US))
(until 5:30 PM)
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5:00 PM
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Neural Network Pruning:
from over-parametrized to under-parametrized networks
- Dr
Michela Paganini
(Facebook AI Research)
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2:00 PM
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Workshop
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David Rousseau
(IJCLab-Orsay)
Pietro Vischia
(Universite Catholique de Louvain (UCL) (BE))
(until 4:00 PM)
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2:00 PM
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Lorentz Equivariant Neural Networks for Particle Physics
-
Alexander Bogatskiy
(University of Chicago)
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2:20 PM
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Graph Neural Network-based Event Classification for Measurement of the Higgs-Top Yukawa Interaction
-
Ryan Roberts
(Lawrence Berkeley National Lab. (US))
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2:40 PM
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Disentangling Boosted Higgs Boson Production Modes with Machine Learning
-
Yi-Lun Chung
(National Tsing Hua University (TW))
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2:45 PM
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Bayesian Neural Networks for Predictions from High Dimensional Theories
-
Braden Kronheim
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4:00 PM
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Walk through
-
David Rousseau
(LAL-Orsay, FR)
(until 6:00 PM)
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4:00 PM
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Deep Dive on Graph Networks for Learning Simulation (Deep Mind)
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Alvaro Sanchez-Gonzalez
(DeepMind)
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5:00 PM
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Tracking GNN Walk Through
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Daniel Thomas Murnane
(Lawrence Berkeley National Lab. (US))
Xiangyang Ju
(Lawrence Berkeley National Lab. (US))
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2:00 PM
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Workshop
-
Riccardo Torre
(CERN)
(until 5:55 PM)
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2:00 PM
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Teaching Machine Learning with ATLAS Open Data
-
Meirin Oan Evans
(University of Sussex (GB))
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2:20 PM
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Active Anomaly Detection for time-domain discoveries
-
Emille Eugenia DE OLIVEIRA ISHIDA
(CNRS)
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2:40 PM
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Generative Adversarial Network for Identifying the Dark Matter Distribution of a Dwarf Spheroidal Galaxy
-
Sung Hak Lim
(Rutgers University)
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3:00 PM
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Pre-Learning a Geometry Using Machine Learning to Accelerate High Energy Physics Detector Simulations
-
Evangelos Kourlitis
(Argonne National Laboratory (US))
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3:05 PM
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High Fidelity Simulation of High Granularity Calorimeters with High Speed
-
Engin Eren
(Deutsches Elektronen-Synchrotron DESY)
|
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3:10 PM
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Graph Convolutional Operators in the the PyTorch JIT
-
Lindsey Gray
(Fermi National Accelerator Lab. (US))
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3:15 PM
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GPU and FPGA as a Service for Machine Learning Inference Accelerations
-
Yu Lou
(University of Washington (US))
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3:20 PM
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--- Coffee Break ---
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3:50 PM
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DisCo: Robust Networks and automated ABCD background estimation
-
David Shih
(Rutgers University)
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4:10 PM
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Decorrelation via Disentanglement
-
Justin Tan
|
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4:30 PM
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Enhancing searches for resonances with machine learning and moment decomposition
-
Ouail Kitouni
(Massachusetts Inst. of Technology (US))
|
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4:35 PM
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Simulation-Assisted Decorrelation for Resonant Anomaly Detection
-
Kees Christian Benkendorfer
(Lawrence Berkeley National Lab. (US))
|
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4:55 PM
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Anomaly Awareness for BSM Searches at the LHC
-
Charanjit Kaur Khosa
|
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5:15 PM
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Model-Independent Detection of New Physics Signals Using Interpretable Semi-Supervised Classifier Tests
-
Purvasha Chakravarti
(Imperial College London)
|
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5:20 PM
|
Conclusion and wrap-up
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