ML4Jets2020

from Wednesday, 15 January 2020 (09:00) to Friday, 17 January 2020 (19:00)


        : Sessions
    /     : Talks
        : Breaks
15 Jan 2020
16 Jan 2020
17 Jan 2020
AM
09:00
Introduction - Ben Nachman (Lawrence Berkeley National Lab. (US)) Tilman Plehn (until 10:40) ()
09:00 Welcome and Logistics - Sebastian Macaluso (New York University) Kyle Stuart Cranmer (New York University (US))   ()
09:10 Theory Introduction (20'+10') - Prof. Maxim Perelstein   ()
09:40 Experiment Introduction (20'+10') - Alison Lister (University of British Columbia (CA))   ()
10:10 ML Introduction (20'+10') - Gilles Louppe (New York University (US))   ()
10:40 --- Coffee break ---
11:10
Architectures - Matthew Schwartz Taoli Cheng (University of Montreal) (until 12:50) ()
11:10 CapsNets Continuing the Convolutional Quest - Sascha Daniel Diefenbacher (Hamburg University (DE))   ()
11:30 Quark-gluon discrimination with point clouds - Vinicius Massami Mikuni (Universitaet Zuerich (CH))   ()
11:50 Two-Point Energy Correlation Spectra Analysis for Top Tagging - Sung Hak Lim (KEK)   ()
12:10 Deep Learning Jet Substructure from Two-Particle Correlation - Dr Yang-Ting Chien (Stony Brook University)   ()
12:30 CLARIANT: Covariant Lorentz Group Architecture for Artificial Neural Networks - Alexander Bogatskiy   ()
09:00
Decorrelation and Semi/Unsupervised approaches - Nhan Viet Tran (Fermi National Accelerator Lab. (US)) Chase Owen Shimmin (Yale University (US)) (until 10:40) ()
09:00 Data ex Machina: Machine Learning with Jets in CMS Open Data - Eric Metodiev (Massachusetts Institute of Technology)   ()
09:20 Variational Autoencoders using EMD - Jack Collins (SLAC)   ()
09:40 Tagger-mass decorrelation: experience within CMS - CMS TBD   ()
10:00 Disco Fever - Gregor Kasieczka (Hamburg University (DE))   ()
10:20 Double DisCo: An Automated ABCD Method - David Shih (Rutgers University)   ()
10:40 --- Coffee break ---
11:10
ML Beyond HEP - Kyle Stuart Cranmer (New York University (US)) (until 12:40) ()
11:10 Optimal Transport - Jonathan Niles-Weed (NYU)   ()
11:40 TBD - Kyunghyun Cho   ()
12:10 Guided discussion   ()
09:00
Machine Learning Inference and Interpretation - Jesse Thaler (MIT) Anja Butter (until 12:21) ()
09:00 Deep-Learning Jets with Uncertainties and More - Michel Luchmann (Universität Heidelberg)   ()
09:19 Bounding high-dimensional uncertainties with adversarial approaches - Chase Owen Shimmin (Yale University (US))   ()
09:38 Omniscient Unfolding via Machine Learning - Patrick Komiske (Massachusetts Institute of Technology)   ()
09:57 GANning away detector effects - Marco Bellagente (Universität Heidelberg)   ()
10:16 --- Coffee break ---
10:46 Metrics and Machine Learning Algorithms for Collider Space - Ms Tianji Cai (University of California, Santa Barbara)   ()
11:05 Layerwise Relevance Propagation for XAI in Jets - Lauren Meryl Hay (The State University of New York SUNY (US)) Garvita Agarwal (The State University of New York SUNY (US))   ()
11:24 Looking into Jets with Machine Learning - Sebastian Macaluso (New York University)   ()
11:43 A Normalizing Flow Model for Boosted Jets - Matthew Drnevich (NYU)   ()
12:02 Realigning the goals of machine learning with the goals of physics - Prasanth Shyamsundar (University of Florida)   ()
PM
12:55 --- Lunch ---
14:30
Generative Models - Jana Schaarschmidt (University of Washington (US)) Martin Erdmann (Rheinisch Westfaelische Tech. Hoch. (DE)) (until 18:00) ()
14:30 DijetGAN: A Generative-Adversarial Network approach for the simulation of QCD Dijet events at the LHC - Serena Palazzo (The University of Edinburgh (GB))   ()
14:50 A generator cell for LHC event GANs - Niclas Eich (RWTH Aachen University (DE))   ()
15:10 How to GAN LHC Events - Ramon Winterhalder (Universität Heidelberg)   ()
15:30 GAN based event subtraction for Monte Carlo methods - Anja Butter   ()
15:50 --- Coffee break ---
16:20 Teaching a Computer to Integrate - Claudius Krause (Fermilab) Christina Gao   ()
16:40 Lund jet images from generative and cycle-consistent adversarial networks - Stefano Carrazza (CERN) Frederic Alexandre Dreyer (Oxford)   ()
17:00 Fast Calorimeter Simulation in ATLAS: FastCaloSimV2 - Sean Joseph Gasiorowski (University of Washington (US))   ()
17:20 Fast Calorimeter Simulation in ATLAS with DNNs - Dalila Salamani (Universite de Geneve (CH))   ()
17:40 Generative Models in CALICE - Engin Eren   ()
12:40 --- Lunch ---
14:10
Anomaly detection (LHCO) - Gregor Kasieczka (Hamburg University (DE)) David Shih (Rutgers University) (until 17:40) ()
14:10 LHCO Introduction and overview - Gregor Kasieczka (Hamburg University (DE)) David Shih (Rutgers University)   ()
14:30 ROB: Reproducible Open Benchmarks for Data Analysis Platform - Sebastian Macaluso (New York University) Heiko Mueller   ()
14:50 Unsupervised new physics searches with data-driven inference - Dr Dillon Barry (Jozef Stefan Institute)   ()
15:10 Tag N’ Train : Combining Autoencoders and CWoLa for Better Unsupervised Searches - Oz Amram (Johns Hopkins University (US))   ()
15:30 Variational Autoencoders for Anomalous Jet Tagging - Taoli Cheng (University of Montreal)   ()
15:50 --- Coffee break ---
16:20 Comparing weak and unsupervised anomaly detection - Pablo Martín   ()
16:40 Outlier Exposure for the BSM searches at LHC - Charanjit Kaur   ()
17:00 LHC Olympics 2020: Columbia University - Alan Mathew Kahn (Columbia University (US))   ()
17:20 LHC Olympics 2020: MIT - Nilai Sarda (MIT)   ()
12:21 --- Lunch ---
13:21
Experimental methods - David Miller (University of Chicago (US)) Maurizio Pierini (CERN) (until 15:35) ()
13:21 Deep Learning based Energy Reconstruction and Event Generation for the CALICE AHCAL - Erik Buhmann (Hamburg University (DE))   ()
13:40 Convolutional neural networks with event images for pileup mitigation - Bernard Brickwedde (Johannes Gutenberg Universitaet Mainz (DE))   ()
13:59 Secondary Vertex finding in Jets with Graph Neural Networks - Jonathan Shlomi (Weizmann Institute of Science (IL))   ()
14:18 Mixture Density Networks for tracking in dense environments on ATLAS - Elham E Khoda (University of British Columbia (CA))   ()
14:37 Beyond 4D Tracking: Cluster Shapes for Track Seeding - Joshua Isaacson (Fermilab)   ()
14:57 Deep learning methods to improve Particle Flow reconstruction - Sanmay Ganguly (Weizmann Institute of Science (IL))   ()
15:16 Machine Learning Based Jet $p_{T}$ Reconstruction in ALICE - Hannah Bossi (Yale University (US))   ()
15:35 --- Coffee break ---
16:05
Applications - Salvatore Rappoccio (The State University of New York SUNY (US)) (until 18:25) ()
16:05 Jet substructure tagging and pileup mitigation - CMS TBD   ()
16:24 Machine learning approaches to the identification of jets originating from heavy-flavor quarks. - Philipp Windischhofer (University of Oxford (GB))   ()
16:43 Searching for long lived particles with a neural-network-based displaced jet tagger - Vilius Cepaitis (Imperial College (GB))   ()
17:03 Jet or Event? - Physics at Future $e^-e^+$ Colliders - Mr Sijun Xu (Department of Physics, The Hong Kong University of Science and Technology)   ()
17:23 The Di-Higgs Photography with Deep Neural Networks - Dr Jeong Han Kim (University of Notre Dame)   ()
17:43 Cornering charming Higgs decays - Mr Joseph Walker (University of Durham )   ()
18:03 Using machine learning to constrain the Higgs total width - Cristina Ana Mantilla Suarez (Johns Hopkins University (US)) Dylan Sheldon Rankin (Massachusetts Inst. of Technology (US))   ()