3rd IML Machine Learning Workshop

from Monday, 15 April 2019 (09:00) to Thursday, 18 April 2019 (20:00)
CERN (500/1-001)

        : Sessions
    /     : Talks
        : Breaks
15 Apr 2019
16 Apr 2019
17 Apr 2019
18 Apr 2019
AM
09:00
Invited keynote talks - Steven Randolph Schramm (Universite de Geneve (CH)) Paul Seyfert (CERN) (until 10:50) (500/1-001 - Main Auditorium)
09:00 Welcome - Steven Randolph Schramm (Universite de Geneve (CH))   (500/1-001 - Main Auditorium)
09:20 Conceptual overview of ML in HEP - Dr Sergei Gleyzer (University of Florida (US))   (500/1-001 - Main Auditorium)
10:05 Future areas of focus for ML in particle physics - Kyle Stuart Cranmer (New York University (US))   (500/1-001 - Main Auditorium)
10:50 --- Coffee break ---
11:15
Joint lecture/seminar - Olaf Behnke (Deutsches Elektronen-Synchrotron (DE)) Louis Lyons (Imperial College (GB)) (until 12:15) (500/1-001 - Main Auditorium)
11:15 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)
09:00
Submitted contributions - Paul Seyfert (CERN) Lorenzo Moneta (CERN) (until 10:45) (500/1-001 - Main Auditorium)
09:00 Daily announcements   (500/1-001 - Main Auditorium)
09:05 Machine Learning Uncertainties with Adversarial Neural Networks - Dr Peter Galler (University of Glasgow)   (500/1-001 - Main Auditorium)
09:25 Decoding Physics Information in DNNs - Taoli Cheng (University of Montreal)   (500/1-001 - Main Auditorium)
09:45 Learning Invariant Representations using Mutual Information Regularization - Mr Justin Tan (University of Melbourne)   (500/1-001 - Main Auditorium)
10:05 Neural networks for the abstraction of the physical symmetries in the nature - Wonsang Cho (Seoul National University)   (500/1-001 - Main Auditorium)
10:25 Containers for Machine Learning in HEP - Matthew Feickert (Southern Methodist University (US))   (500/1-001 - Main Auditorium)
10:45 --- Coffee break ---
11:15
Invited plenary talk (until 12:30) (500/1-001 - Main Auditorium)
11:15 The information theory of Deep Learning - Prof. Naftali Tishby (Hebrew University of Jerusalem)   (500/1-001 - Main Auditorium)
09:00
Submitted contributions - Paul Seyfert (CERN) Lorenzo Moneta (CERN) (until 12:30) (500/1-001 - Main Auditorium)
09:00 Daily announcements   (500/1-001 - Main Auditorium)
09:05 Applying Generative Models to Scientific Research - Fedor Ratnikov (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
09:35 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)
09:55 High Granularity Calorimeter Simulation using Generative Adversarial Networks - Gul Rukh Khattak (University of Peshawar (PK))   (500/1-001 - Main Auditorium)
10:15 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 --- Coffee break ---
11:05 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 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 Event Generation and Statistical Sampling with Deep Generative Models - Sydney Otten (Radboud Universiteit Nijmegen)   (500/1-001 - Main Auditorium)
12:05 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)
09:00
Tutorials - Lorenzo Moneta (CERN) Rudiger Haake (Yale University (US)) (until 13:10) (500/1-001 - Main Auditorium)
09:00 Introduction to the basics of deep learning - Yannik Alexander Rath (RWTH Aachen University (DE))   (500/1-001 - Main Auditorium)
10:30 --- Coffee break ---
11:00 Physics inspired Autonomous Feature Engineering - Marcel Rieger (RWTH Aachen University (DE))   (500/1-001 - Main Auditorium)
12:00 Traditional approach to network architecture optimisation - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
12:30 Differentiable architecture search - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
PM
12:30 --- Lunch ---
14:00
Industry talks and panel - Markus Stoye (CERN) David Rousseau (LAL-Orsay, FR) (until 18:00) (500/1-001 - Main Auditorium)
14:00 Introduction - Markus Stoye (CERN)   (500/1-001 - Main Auditorium)
14:20 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)
15:05 Google DeepMind: Compressing neural networks - Dr Tim Genewein (DeepMind)   (500/1-001 - Main Auditorium)
16:00 --- Coffee break ---
16:30 B12 Consulting: Big value out of small data - Dr Michel Herquet (B12)   (500/1-001 - Main Auditorium)
17:05 Industry panel - Dr Tim Genewein (DeepMind) Dr Michel Herquet (B12)   (500/1-001 - Main Auditorium)
18:00 --- Welcome reception ---
12:30 --- Lunch ---
13:59
Q&A with Prof. Naftali Tishby - Louis Lyons (Imperial College (GB)) (until 15:00) (31/3-004 - IT Amphitheatre)
14:15 Q&A with Prof. Naftali Tishby - Prof. Naftali Tishby (Hebrew University of Jerusalem)   (31/3-004 - IT Amphitheatre)
14:00
Submitted contributions - David Rousseau (LAL-Orsay, FR) Steven Randolph Schramm (Universite de Geneve (CH)) (until 16:00) (500/1-001 - Main Auditorium)
14:00 Novelty Detection Meets Collider Physics - Ms Ying-Ying Li (HKUST)   (500/1-001 - Main Auditorium)
14:30 Uncertain Networks - Jennifer Thompson (ITP Heidelberg)   (500/1-001 - Main Auditorium)
15:00 Exploring SMEFT in VH channel with Machine Learning - Charanjit Kaur Khosa   (500/1-001 - Main Auditorium)
15:30 The Tracking Machine Learning challenge - David Rousseau (LAL-Orsay, FR)   (500/1-001 - Main Auditorium)
16:00 --- Coffee break ---
16:30
CERN Colloquium (until 18:00) (500/1-001 - Main Auditorium)
16:30 Gauge Fields in Deep Learning   (500/1-001 - Main Auditorium)
12:30 --- Lunch ---
14:00
Submitted contributions - Rudiger Haake (Yale University (US)) Steven Randolph Schramm (Universite de Geneve (CH)) (until 18:40) (500/1-001 - Main Auditorium)
14:00 A hybrid deep learning approach to vertexing - Henry Fredrick Schreiner (University of Cincinnati (US))   (500/1-001 - Main Auditorium)
14:20 Feature ranking based on subtraction methods - Paul Glaysher (DESY)   (500/1-001 - Main Auditorium)
14:40 ML Techniques for heavy flavour identification in CMS - Emil Sorensen Bols (Vrije Universiteit Brussel (BE))   (500/1-001 - Main Auditorium)
15:10 ParticleNet: Jet Tagging via Particle Clouds - Huilin Qu (Univ. of California Santa Barbara (US))   (500/1-001 - Main Auditorium)
15:30 Learning representations of irregular particle-detector geometry with distance-weighted graph networks - Jan Kieseler (CERN)   (500/1-001 - Main Auditorium)
16:00 --- Coffee break ---
16:30 GroomRL: jet grooming through reinforcement learning - Frederic Alexandre Dreyer (Oxford)   (500/1-001 - Main Auditorium)
16:50 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)
17:10 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)
17:30 Close-out - Steven Randolph Schramm (Universite de Geneve (CH))   (500/1-001 - Main Auditorium)
13:10 --- Lunch ---
15:00
Tutorials - Rudiger Haake (Yale University (US)) David Rousseau (LAL-Orsay, FR) (until 18:30) (500/1-001 - Main Auditorium)
15:00 Bayesian approach to network design - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
15:30 Bayesian dropout explanation and examples - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   (500/1-001 - Main Auditorium)
16:15 --- Coffee break ---
16:45 Advanced Generative Adversarial Network Techniques - Jonas Glombitza (Rheinisch-Westfaelische Tech. Hoch. (DE))   (500/1-001 - Main Auditorium)