ML4Jets2020

from Wednesday, January 15, 2020 (8:30 AM) to Friday, January 17, 2020 (7:00 PM)
Kimmel Center for University Life (KC 802 )

        : Sessions
    /     : Talks
        : Breaks
Jan 15, 2020
Jan 16, 2020
Jan 17, 2020
AM
8:30 AM
Registration (until 9:00 AM) (KC 802)
9:00 AM
Introduction - Ben Nachman (Lawrence Berkeley National Lab. (US)) Tilman Plehn (until 10:40 AM)
9:00 AM Welcome and Logistics - Kyle Stuart Cranmer (New York University (US)) Sebastian Macaluso (New York University)  
9:10 AM Theory Introduction (20'+10') - Prof. Maxim Perelstein  
9:40 AM Experiment Introduction (20'+10') - Alison Lister (University of British Columbia (CA))  
10:10 AM ML Introduction (20'+10') - Gilles Louppe (New York University (US))  
10:40 AM --- Coffee break ---
11:10 AM
Architectures - Taoli Cheng (University of Montreal) Matthew Schwartz (until 12:50 PM)
11:10 AM CapsNets Continuing the Convolutional Quest - Sascha Daniel Diefenbacher (Hamburg University (DE))  
11:30 AM Quark-gluon discrimination with point clouds - Vinicius Massami Mikuni (Universitaet Zuerich (CH))  
11:50 AM Modeling a top jet classifier with two-point energy correlation and geometry of soft emission - Sung Hak Lim (KEK)  
12:10 PM Deep Learning Jet Substructure from Two-Particle Correlation - Dr Yang-Ting Chien (Stony Brook University)  
12:30 PM CLARIANT: Covariant Lorentz Group Architecture for Artificial Neural Networks - Alexander Bogatskiy  
9:00 AM
Decorrelation and Semi/Unsupervised approaches - Chase Owen Shimmin (Yale University (US)) Nhan Viet Tran (Fermi National Accelerator Lab. (US)) (until 11:00 AM)
9:00 AM Data ex Machina: Machine Learning with Jets in CMS Open Data - Eric Metodiev (Massachusetts Institute of Technology)  
9:20 AM Representation Learning for Collider Events - Jack Collins (SLAC)  
9:40 AM Tagger-mass decorrelation: experience within CMS - Huilin Qu (Univ. of California Santa Barbara (US))  
10:00 AM Disco Fever - Gregor Kasieczka (Hamburg University (DE))  
10:20 AM A Normalizing Flow Model for Boosted Jets - Matthew Drnevich (NYU)  
10:39 AM Metrics and Machine Learning Algorithms for Collider Space - Ms Tianji Cai (University of California, Santa Barbara)  
11:00 AM --- Coffee break ---
11:30 AM
ML Beyond HEP - Kyle Stuart Cranmer (New York University (US)) (until 1:00 PM)
11:30 AM Optimal Transport - Jonathan Niles-Weed (NYU)  
12:00 PM Beyond monotonic, autoregressive sequence modeling - Kyunghyun Cho  
12:30 PM Guided discussion  
9:00 AM
Machine Learning Inference and Interpretation - Anja Butter Jesse Thaler (MIT) (until 11:50 AM) (KC 914)
9:00 AM Deep-Learning Jets with Uncertainties and More - Michel Luchmann (Universität Heidelberg)  
9:20 AM Bounding high-dimensional uncertainties with adversarial approaches - Chase Owen Shimmin (Yale University (US))  
9:40 AM OmniFold: Simultaneously Unfolding All Observables - Patrick Komiske (Massachusetts Institute of Technology)  
10:00 AM GANning away detector effects - Marco Bellagente (Universität Heidelberg)  
10:20 AM --- Coffee break ---
10:50 AM Looking into Jets with Machine Learning - Sebastian Macaluso (New York University)  
11:10 AM Realigning the goals of machine learning with the goals of physics - Prasanth Shyamsundar (University of Florida)  
11:30 AM ROB: Reproducible Open Benchmarks for Data Analysis Platform - Heiko Mueller Sebastian Macaluso (New York University)  
11:50 AM --- Lunch ---
PM
12:50 PM --- Lunch ---
2:10 PM
Generative Models - Jana Schaarschmidt (University of Washington (US)) Martin Erdmann (Rheinisch Westfaelische Tech. Hoch. (DE)) (until 5:45 PM)
2:10 PM Introduction - Martin Erdmann (Rheinisch Westfaelische Tech. Hoch. (DE)) Jana Schaarschmidt (University of Washington (US))  
2:15 PM DijetGAN: A Generative-Adversarial Network approach for the simulation of QCD Dijet events at the LHC - Serena Palazzo (The University of Edinburgh (GB))  
2:35 PM A generator cell for LHC event GANs - Niclas Eich (RWTH Aachen University (DE))  
2:55 PM How to GAN LHC Events - Ramon Winterhalder (Universität Heidelberg)  
3:15 PM GAN based event subtraction for Monte Carlo methods - Anja Butter  
3:35 PM Teaching a Computer to Integrate - Christina Gao Claudius Krause (Fermilab)  
3:55 PM --- Coffee break ---
4:25 PM Lund jet images from generative and cycle-consistent adversarial networks - Stefano Carrazza (CERN) Frederic Alexandre Dreyer (Oxford)  
4:45 PM Fast Calorimeter Simulation in ATLAS: FastCaloSimV2 - Sean Joseph Gasiorowski (University of Washington (US))  
5:05 PM Fast Calorimeter Simulation in ATLAS with DNNs - Dalila Salamani (Universite de Geneve (CH))  
5:25 PM Generative Models in CALICE - Engin Eren  
7:00 PM
Workshop Dinner (until 9:00 PM)
1:00 PM --- Lunch ---
2:20 PM
Anomaly detection (LHCO) - David Shih (Rutgers University) Gregor Kasieczka (Hamburg University (DE)) (until 6:10 PM)
2:30 PM LHCO Introduction and overview - Gregor Kasieczka (Hamburg University (DE)) David Shih (Rutgers University)  
2:50 PM Unsupervised new physics searches with data-driven inference - Dr Dillon Barry (Jozef Stefan Institute)  
3:10 PM Tag N’ Train : Combining Autoencoders and CWoLa for Better Unsupervised Searches - Oz Amram (Johns Hopkins University (US))  
3:30 PM Variational Autoencoders for Anomalous Jet Tagging - Taoli Cheng (University of Montreal)  
3:50 PM --- Coffee break ---
4:20 PM Comparing weak and unsupervised anomaly detection - Pablo Martín  
4:40 PM LHC Olympics 2020: Columbia University - Alan Mathew Kahn (Columbia University (US))  
5:00 PM LHC Olympics 2020: MIT - Nilai Sarda (MIT)  
5:20 PM LHC Olympics 2020: Berkeley Cosmology - George Stein  
5:40 PM LHCO2020: Outcome of the Challenge - David Shih (Rutgers University) Gregor Kasieczka (Hamburg University (DE)) Ben Nachman (Lawrence Berkeley National Lab. (US))  
1:00 PM
Experimental methods - Philip Coleman Harris (Massachusetts Inst. of Technology (US)) (until 2:50 PM) (KC 914)
1:00 PM Deep Learning based Energy Reconstruction and Event Generation for the CALICE AHCAL - Erik Buhmann (Hamburg University (DE))  
1:20 PM Convolutional neural networks with event images for pileup mitigation [cancelled due to illness] - Bernard Brickwedde (Johannes Gutenberg Universitaet Mainz (DE))  
1:30 PM Secondary Vertex finding in Jets with Graph Neural Networks - Eilam Gross (Weizmann Institute of Science (IL))  
1:50 PM Mixture Density Networks for tracking in dense environments on ATLAS - Elham E Khoda (University of British Columbia (CA))  
2:10 PM Deep learning methods to improve Particle Flow reconstruction - Sanmay Ganguly (Weizmann Institute of Science (IL))  
2:30 PM Machine Learning Based Jet $p_{T}$ Reconstruction in ALICE - Hannah Bossi (Yale University (US))  
2:50 PM --- Coffee break ---
3:20 PM
Applications - Dan Guest (University of California Irvine (US)) Christine Angela McLean (SUNY Buffalo) (until 5:40 PM) (KC 914)
3:20 PM Jet substructure tagging and pileup mitigation - Alejandro Gomez Espinosa (ETH Zurich (CH))  
3:40 PM Machine learning approaches to the identification of jets originating from heavy-flavor quarks. - Philipp Windischhofer (University of Oxford (GB))  
4:00 PM Searching for long lived particles with a neural-network-based displaced jet tagger - Robert John Bainbridge (Imperial College (GB))  
4:20 PM Jet or Event? - Physics at Future $e^-e^+$ Colliders - Mr Sijun Xu (Department of Physics, The Hong Kong University of Science and Technology)  
4:40 PM The Di-Higgs Photography with Deep Neural Networks - Dr Jeong Han Kim (University of Notre Dame)  
5:00 PM Cornering charming Higgs decays - Mr Joseph Walker (University of Durham )  
5:20 PM 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))  
5:40 PM Closeout - Tilman Plehn