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09:00
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Arrival / Registration
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10:00
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Welcome from Lorentz Center
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10:10
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Welcome, Workshop Structure and Objectives
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Sascha Caron
(Nikhef National institute for subatomic physics (NL))
()
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10:20
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Dark Matter overview
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Nicolao Fornengo
(University of Torino and INFN)
()
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11:05
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Introduction into Deep Learning and Image Analysis
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Max Welling
()
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11:50
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First ideas to connect Astronomical data, Deep Learning and Image Analysis
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German Gomez-Vargas
(Pontifical Catholic University of Chile)
German Arturo Gomez Vargas
(Universidad Autonoma de Madrid)
()
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09:00
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Results of yesterdays workgroups on Deep Learning, Image Analysis and astronomical Dark Matter data
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09:30
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Astronomical Dark Matter measurements and Challenges
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David Richard Harvey
(EPFL - EPF Lausanne)
()
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10:15
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--- Coffee break ---
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10:35
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Introduction into direct and indirect Dark Matter searches and their challenges
- Dr
Marco Regis
(INFN - National Institute for Nuclear Physics)
Marco Regis
()
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11:20
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Introduction into unsupervised learning
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Erzsébet Merényi
()
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09:15
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Results of yesterdays workgroups on unsupervised learning, direct and indirect DM searches
()
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09:45
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New approaches in semi-supervised learning
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Kristiaan Pelckmans
()
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10:30
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--- Coffee ---
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11:00
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First ideas: Supervised DNNs for reconstruction in LHC data
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Markus Stoye
(CERN)
()
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11:45
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Recent results : Dark Matter searches at LHC
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Renjie Wang
(LPNHE-Paris CNRS/IN2P3 (FR))
Renjie Wang
(LPNHE-Paris, CNRS/IN2P3 (FR))
()
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09:00
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Results of yesterdays workgroups on supervised learning and DM searches at the LHC
()
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09:30
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Introduction into theory models for Dark Matter particles
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Andrea de Simone
()
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10:15
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--- Coffee ---
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10:35
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OpenML/AutoML: Organizing machine learning data and learning to learn better models
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Joaquin Vanschoren
()
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11:20
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Adversarial Games for Particle Physics
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Gilles Louppe
(New York University (US))
()
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09:30
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Open discussion: what have we leart? What next?
()
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11:30
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--- Coffee and Goodbye ---
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12:15
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Discussion: First connections ?
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12:35
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--- Lunch ---
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14:00
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Cross link: Deep Learning in High Energy Physics
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Amir Farbin
(University of Texas at Arlington (US))
()
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14:45
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Discussion: New ideas ?
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15:05
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--- Coffee break ---
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15:35
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Work in subgroups : Finding new projects in Deep Learning / Image Analysis
()
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16:30
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The hunt for stellar-mass DM clumps: applying the statistical machine learning techniques to strong microlensing events
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Elena Fedorova
()
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16:45
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Fast model discrimination with Euclideanized signals
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Christoph Weniger
(University of Amsterdam)
()
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17:00
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--- Wine and Cheese Party at Common Room (maybe Posters) ---
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12:05
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Discussion Unsupervised Leaning for Dark Matter
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12:25
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--- Lunch ---
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13:55
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First ideas to use Machine Learning in direct Dark Matter searches
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Christopher Tunnell
(Enrico Fermi Institute-University of Chicago-Unknown)
Andrew Brown
(MIT) Dr
Christopher Tunnell
(University of Chicago)
Andrew Brown
(Nikhef)
()
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14:25
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Discussion: New ideas ?
()
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14:40
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First ideas to use Machine Learning in indirect detection
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Luc Hendriks
(Nikhef)
()
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15:10
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Discussion: New ideas?
()
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15:30
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--- Coffee ---
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15:50
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Work in subgroups
()
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16:50
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Characterization of the Local Universe via angular cross-correlations
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Simone Ammazzalorso
(University of Turin)
()
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17:05
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Dark matter searches in dwarf irregular galaxies
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Viviana Gammaldi
(SISSA)
()
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12:00
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Machine Learning for SHiP and NEWS experiments
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Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
()
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12:30
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--- Lunch ---
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14:00
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Miscellaneous thoughts on Machine Learning & Dark Matter
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Kyle Stuart Cranmer
(New York University (US))
()
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14:45
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Discussion: New ideas? Reinforcement Learning?
()
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15:05
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--- Coffee ---
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15:25
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Work on projects in subgroups
()
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16:10
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Data-driven constraints on dark matter from dwarf galaxies
- Mr
Bryan Zaldivar
(LAPTh, Annecy)
()
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16:25
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Fast Forecasting for Counting Experiments
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Tom Edwards
()
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16:40
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Estimating the parameters of gravitational lenses with deep learning
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laurence perreault levasseur
(Stanford University)
()
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17:00
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--- Conference Dinner (Boat trip) ---
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12:05
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Discussion: Further ideas?
()
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12:25
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--- Lunch ---
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13:55
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Dark Matter model exploration and first ML ideas
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Martin John White
(University of Adelaide (AU))
()
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14:40
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How to find Natural Supersymmetric Dark Matter?
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Melissa van Beekveld
(R)
()
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14:55
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BSM-AI (SUSY-AI) and iDarkSurvey: Learning (from) high-dimensional models
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Bob Stienen
(Radboud University)
()
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15:10
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Using Deep Learning to predict Electroweakino production cross-sections at the LHC
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Sydney Otten
(RWTH Aachen)
()
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15:25
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--- Coffee ---
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15:45
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Discussion: New ideas?
()
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16:05
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Work in subgroups
()
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