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09:00
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Introduction
-
Frank Schroeder
(University of Delaware / Karlsruhe Institute of Technology)
(until 09:15)
()
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09:15
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Tuesday
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Frank Schroeder
(University of Delaware / Karlsruhe Institute of Technology)
(until 10:30)
()
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09:15
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Deep learning in astroparticle physics
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Jonas Glombitza
(RWTH AACHEN UNIVERSITY)
()
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10:00
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Machine Learning for High-Energy Physics Reconstruction and Analysis
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Sergei Gleyzer
()
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10:30
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--- Coffee Break ---
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11:00
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Tuesday
(until 12:30)
()
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11:00
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Exploitation of Symmetries and Domain Knowledge in Deep Learning Architectures
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Mirco Huennefeld
(Universität Dortmund)
()
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11:45
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Composition Analysis of cosmic-rays at IceCube Observatory, using Graph Neural Networks
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Paras Koundal
(Karlsruhe Institute of Technology)
()
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09:00
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Wednesday
(until 10:30)
()
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09:00
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Machine learning based event reconstruction in Telescope Array surface detector
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Oleg Kalashev
(INR RAS Moscow)
()
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09:45
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State-of-art deep learning technologies and their application to air-shower reconstruction
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Vladimir Sotnikov
(JetBrains Research)
()
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10:30
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--- Coffee Break ---
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11:00
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Wednesday
(until 12:30)
()
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11:00
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Deep Learning for Air Shower Reconstruction at the Pierre Auger Observatory
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Jonas Glombitza
(RWTH AACHEN UNIVERSITY)
for the Pierre Auger Collaboration
()
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11:30
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Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks
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Juan Miguel Carceller
(University College London)
()
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12:00
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Neural Network Approaches for Event Classification Onboard EUSO-SPB2
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George Filippatos
(Colorado School of Mines)
()
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09:00
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Thursday
(until 10:30)
()
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09:00
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Machine learning in Baikal-GVD
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Ivan Kharuk
(Institute for Nuclear Research RAS)
()
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09:35
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Towards mass composition study with KASCADE using deep learning
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Daniil Reutsky
(Moscow Institute of Physics and Technology)
()
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09:55
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IACT event reconstruction with deep learning: some progress, lessons learned, and outlook from CTLearn
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Daniel Nieto
(Instituto de Física de Partículas y del Cosmos and Departamento de EMFTEL, Universidad Complutense de Madrid)
()
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10:30
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--- Coffee Break ---
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11:00
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Thursday
(until 12:30)
()
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11:00
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Search for optimal deep neural network architecture for gamma detection at KASCADE
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Margarita Tsobenko
(Higher School of Economics University - St. Petersburg)
()
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11:20
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Photon flux calculation using Deep Learning
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Jigar Bhanderi
()
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11:55
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Improving the gamma-hadron separation for air showers at the IceCube Neutrino Observatory
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Federico Bontempo
(Karlsruhe Institute of Technology)
()
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17:00
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Registration
(until 17:30)
()
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17:30
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Welcome Reception
(until 19:00)
()
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12:30
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--- Lunch ---
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14:00
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Tuesday
(until 15:30)
()
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14:00
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Measurement of the high-energy muon multiplicity in cosmic-ray air showers with IceTop and IceCube using neural networks
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Stef Verpoest
(University of Gent)
()
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14:30
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Air shower reconstruction using a Graph Neural Network for the IceAct telescopes
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Larissa Paul
(Marquette University)
()
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15:00
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Cosmic ray mass composition study using a Random Forest applied to data from the IceAct telescopes
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Larissa Paul
(Marquette University)
()
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15:15
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Pattern Recognition for Multiple Interactions in a Neutron Monitor
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P.-S. Mangeard
(University of Delaware)
()
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15:30
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--- Coffee Break ---
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16:00
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Tuesday
(until 17:30)
()
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16:00
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Composition of 100 TeV - 100 PeV Cosmic Rays with IceCube and IceTop using Boosted Decision Trees
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Julian Saffer
(Karlsruhe Institute of Technology)
()
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16:30
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Cosmic rays primary energy estimation using Machine Learning and combined reconstruction
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Diana Leon Silverio
(South Dakota School of Mines and Technology)
()
|
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17:00
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Energy Reconstruction with Convolutional Neural Networks in IceTop
-
Frank McNally
(Mercer University)
()
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12:30
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--- Lunch ---
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14:00
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Wednesday
(until 15:30)
()
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14:00
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CORSIKA and CONEX for air shower simulations
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Tanguy Pierog
(Karlsruhe Institute of Technology (KIT), IAP)
()
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14:45
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CORSIKA 8: A modern framework for high-energy cascade simulations
-
Remy Prechelt
(University of Hawai'i)
()
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15:30
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--- Coffee Break ---
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16:00
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Wednesday
(until 17:30)
()
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16:00
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Machine Learning and Artificial Intelligence in Physics: Overview and Applications
-
Gregory Dobler
(University of Delaware)
()
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12:30
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--- Lunch ---
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14:00
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Thursday
(until 15:30)
()
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14:00
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Open questions in deep learning techniques for the radio detection
-
Dmitriy Kostunin
(DESY)
()
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14:45
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Deep Learning for Classification and Denoising of Cosmic-Ray Radio Signals
-
Abdul Rehman
(University of Delaware)
()
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15:15
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Training Neural Networks to Classify and Denoise Cosmic-Ray Radio Signals Using Background Measured at the South Pole
-
Dana Kullgren
(University of Delaware)
()
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15:30
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--- Coffee Break ---
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16:00
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Thursday
(until 17:30)
()
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16:00
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Crowdsourcing your training labels with Zooniverse
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Lucy Fortson
(University of Minnesota)
()
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16:30
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What slow down cosmic ray analysis and what can we do about them?
-
Xinhua Bai
(South Dakota School of Mines and Technology)
()
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16:55
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Workshop on Machine learning for Cosmic-Ray Air Showers - Summary & Outlook
-
Matthias Plum
(Marquette University)
()
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17:20
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Good Bye
-
Frank Schroeder
(University of Delaware / Karlsruhe Institute of Technology)
()
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