3rd IML Machine Learning Workshop

from Monday, April 15, 2019 (9:00 AM) to Thursday, April 18, 2019 (8:00 PM)
CERN (500/1-001)

        : Sessions
    /     : Talks
        : Breaks
Apr 15, 2019
Apr 16, 2019
Apr 17, 2019
Apr 18, 2019
AM
9:00 AM
Invited keynote talks - Steven Randolph Schramm (Universite de Geneve (CH)) Paul Seyfert (CERN) (until 10:50 AM) (500/1-001 - Main Auditorium)
9:00 AM Welcome - Steven Randolph Schramm (Universite de Geneve (CH))   (500/1-001 - Main Auditorium)
9:20 AM Conceptual overview of ML in HEP - Dr Sergei Gleyzer (University of Florida (US))   (500/1-001 - Main Auditorium)
10:05 AM Future areas of focus for ML in particle physics - Kyle Stuart Cranmer (New York University (US))   (500/1-001 - Main Auditorium)
10:50 AM --- Coffee break ---
11:15 AM
Joint lecture/seminar - Olaf Behnke (Deutsches Elektronen-Synchrotron (DE)) Louis Lyons (Imperial College (GB)) (until 12:15 PM) (500/1-001 - Main Auditorium)
11:15 AM On the Statistical Mechanics and Information Theory of Deep Learning for Particle Physicists - Prof. Naftali Tishby (Hebrew University of Jerusalem)   (500/1-001 - Main Auditorium)
9:00 AM
Submitted contributions - Paul Seyfert (CERN) Lorenzo Moneta (CERN) (until 10:45 AM) (500/1-001 - Main Auditorium)
9:00 AM Daily announcements   (500/1-001 - Main Auditorium)
9:05 AM Machine Learning Uncertainties with Adversarial Neural Networks - Dr Peter Galler (University of Glasgow)   (500/1-001 - Main Auditorium)
9:25 AM Decoding Physics Information in DNNs - Taoli Cheng (University of Montreal)   (500/1-001 - Main Auditorium)
9:45 AM Learning Invariant Representations using Mutual Information Regularization - Mr Justin Tan (University of Melbourne)   (500/1-001 - Main Auditorium)
10:05 AM Neural networks for the abstraction of the physical symmetries in the nature - Wonsang Cho (Seoul National University)   (500/1-001 - Main Auditorium)
10:25 AM Containers for Machine Learning in HEP - Matthew Feickert (Southern Methodist University (US))   (500/1-001 - Main Auditorium)
10:45 AM --- Coffee break ---
11:15 AM
Invited plenary talk (until 12:30 PM) (500/1-001 - Main Auditorium)
11:15 AM The information theory of Deep Learning - Prof. Naftali Tishby (Hebrew University of Jerusalem)   (500/1-001 - Main Auditorium)
9:00 AM
Submitted contributions - Paul Seyfert (CERN) Lorenzo Moneta (CERN) (until 12:30 PM) (500/1-001 - Main Auditorium)
9:00 AM Daily announcements   (500/1-001 - Main Auditorium)
9:05 AM Applying Generative Models to Scientific Research - Fedor Ratnikov (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
9:35 AM DijetGAN: A Generative-Adversarial Network Approach for the Simulation of QCD Dijet Events at the LHC - Serena Palazzo (The University of Edinburgh (GB))   (500/1-001 - Main Auditorium)
9:55 AM High Granularity Calorimeter Simulation using Generative Adversarial Networks - Gul Rukh Khattak (University of Peshawar (PK))   (500/1-001 - Main Auditorium)
10:15 AM Deep generative models for fast shower simulation in ATLAS - Aishik Ghosh (Centre National de la Recherche Scientifique (FR))   (500/1-001 - Main Auditorium)
10:35 AM --- Coffee break ---
11:05 AM Fast Simulation Using Generative Adversarial Network in LHCB - Artem Maevskiy (National Research University Higher School of Economics (RU))   (500/1-001 - Main Auditorium)
11:25 AM Model-Assisted GANs for the optimisation of simulation parameters and as an algorithm for fast Monte Carlo production - Mr Saul Alonso Monsalve (CERN)   (500/1-001 - Main Auditorium)
11:45 AM Event Generation and Statistical Sampling with Deep Generative Models - Sydney Otten (Radboud Universiteit Nijmegen)   (500/1-001 - Main Auditorium)
12:05 PM LUMIN - a deep learning and data science ecosystem for high-energy physics - Giles Chatham Strong (LIP Laboratorio de Instrumentacao e Fisica Experimental de Part)   (500/1-001 - Main Auditorium)
9:00 AM
Tutorials - Lorenzo Moneta (CERN) Rudiger Haake (Yale University (US)) (until 1:10 PM) (500/1-001 - Main Auditorium)
9:00 AM Introduction to the basics of deep learning - Yannik Alexander Rath (RWTH Aachen University (DE))   (500/1-001 - Main Auditorium)
10:30 AM --- Coffee break ---
11:00 AM Physics inspired Autonomous Feature Engineering - Marcel Rieger (RWTH Aachen University (DE))   (500/1-001 - Main Auditorium)
12:00 PM Traditional approach to network architecture optimisation - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
12:30 PM Differentiable architecture search - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
PM
12:30 PM --- Lunch ---
2:00 PM
Industry talks and panel - Markus Stoye (CERN) David Rousseau (LAL-Orsay, FR) (until 6:00 PM) (500/1-001 - Main Auditorium)
2:00 PM Introduction - Markus Stoye (CERN)   (500/1-001 - Main Auditorium)
2:20 PM Amazon AI: Tensor and Higher-Order Generalizations of the GSVD with Applications to Personalized Cancer Medicine - Dr Priya Ponnapalli (Amazon AI)   (500/1-001 - Main Auditorium)
3:05 PM Google DeepMind: Compressing neural networks - Dr Tim Genewein (DeepMind)   (500/1-001 - Main Auditorium)
4:00 PM --- Coffee break ---
4:30 PM B12 Consulting: Big value out of small data - Dr Michel Herquet (B12)   (500/1-001 - Main Auditorium)
5:05 PM Industry panel - Dr Michel Herquet (B12) Dr Tim Genewein (DeepMind)   (500/1-001 - Main Auditorium)
6:00 PM --- Welcome reception ---
12:30 PM --- Lunch ---
1:59 PM
Q&A with Prof. Naftali Tishby - Louis Lyons (Imperial College (GB)) (until 3:00 PM) (31/3-004 - IT Amphitheatre)
2:15 PM Q&A with Prof. Naftali Tishby - Prof. Naftali Tishby (Hebrew University of Jerusalem)   (31/3-004 - IT Amphitheatre)
2:00 PM
Submitted contributions - David Rousseau (LAL-Orsay, FR) Steven Randolph Schramm (Universite de Geneve (CH)) (until 4:00 PM) (500/1-001 - Main Auditorium)
2:00 PM Novelty Detection Meets Collider Physics - Ms Ying-Ying Li (HKUST)   (500/1-001 - Main Auditorium)
2:30 PM Uncertain Networks - Jennifer Thompson (ITP Heidelberg)   (500/1-001 - Main Auditorium)
3:00 PM Exploring SMEFT in VH channel with Machine Learning - Charanjit Kaur Khosa   (500/1-001 - Main Auditorium)
3:30 PM The Tracking Machine Learning challenge - David Rousseau (LAL-Orsay, FR)   (500/1-001 - Main Auditorium)
4:00 PM --- Coffee break ---
4:30 PM
CERN Colloquium (until 6:00 PM) (500/1-001 - Main Auditorium)
4:30 PM Gauge Fields in Deep Learning   (500/1-001 - Main Auditorium)
12:30 PM --- Lunch ---
2:00 PM
Submitted contributions - Rudiger Haake (Yale University (US)) Steven Randolph Schramm (Universite de Geneve (CH)) (until 6:40 PM) (500/1-001 - Main Auditorium)
2:00 PM A hybrid deep learning approach to vertexing - Henry Fredrick Schreiner (University of Cincinnati (US))   (500/1-001 - Main Auditorium)
2:20 PM Feature ranking based on subtraction methods - Paul Glaysher (DESY)   (500/1-001 - Main Auditorium)
2:40 PM ML Techniques for heavy flavour identification in CMS - Emil Sorensen Bols (Vrije Universiteit Brussel (BE))   (500/1-001 - Main Auditorium)
3:10 PM ParticleNet: Jet Tagging via Particle Clouds - Huilin Qu (Univ. of California Santa Barbara (US))   (500/1-001 - Main Auditorium)
3:30 PM Learning representations of irregular particle-detector geometry with distance-weighted graph networks - Jan Kieseler (CERN)   (500/1-001 - Main Auditorium)
4:00 PM --- Coffee break ---
4:30 PM GroomRL: jet grooming through reinforcement learning - Frederic Alexandre Dreyer (Oxford)   (500/1-001 - Main Auditorium)
4:50 PM NeuralRinger: An Ensemble of Neural Networks Fed from Calorimeter Ring Sums for Triggering on Electrons - Werner Spolidoro Freund (Federal University of of Rio de Janeiro (BR))   (500/1-001 - Main Auditorium)
5:10 PM Fast Deep Learning on FPGAs for the Phase-II L0 Muon Barrel Trigger of the ATLAS Experiment - Luigi Sabetta (Sapienza Universita e INFN, Roma I (IT))   (500/1-001 - Main Auditorium)
5:30 PM Close-out - Steven Randolph Schramm (Universite de Geneve (CH))   (500/1-001 - Main Auditorium)
1:10 PM --- Lunch ---
3:00 PM
Tutorials - Rudiger Haake (Yale University (US)) David Rousseau (LAL-Orsay, FR) (until 6:30 PM) (500/1-001 - Main Auditorium)
3:00 PM Bayesian approach to network design - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
3:30 PM Bayesian dropout explanation and examples - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
4:15 PM --- Coffee break ---
4:45 PM Advanced Generative Adversarial Network Techniques - Jonas Glombitza (Rheinisch-Westfaelische Tech. Hoch. (DE))   (500/1-001 - Main Auditorium)