ML4Jets2021

Session

Datasets

Jul 7, 2021, 8:00 PM

Conveners

Datasets

• Gregor Kasieczka (Hamburg University (DE))
• Tobias Golling (Universite de Geneve (CH))

58. Implementation of Jupyter Notebooks into The Reproducible Open Benchmarks for Data Analysis Platform (ROB)

Aaron Wang, Heiko Mueller

7/7/21, 8:00 PM

The Reproducible Open Benchmarks for Data Analysis Platform (ROB) is a platform that allows for the evaluation of different data analysis algorithms in a controlled competition-style format [1]. One example for such a comparison and evaluation of different algorithms is the “The Machine Learning Landscape of Top Taggers” paper, which compiled and compared multiple different top tagger neural...

66. Shared Data and Algorithms for Deep Learning in Fundamental Physics

William Korcari (Hamburg University (DE))

7/7/21, 8:20 PM

We introduce a collection of datasets from fundamental physics research including particle physics, astroparticle physics, hadron, and nuclear physics for supervised machine learning studies. These datasets, containing hadronic top quarks, cosmic air showers, phase transitions in the hadronic matter, and generator-level histories, are combined and made public to simplify future work on...

91. Introduction to Anomaly Detection Challenge

Katya Govorkova (CERN)

7/7/21, 8:40 PM

The data challenge is "anomaly detection @ 40 MHz" for which the biggest concern
is to fit an algorithm in the tight constraints, which are presented in the talk.
Considering as a benchmark an inclusive data stream, which has been pre-filtered
by requiring the presence of one lepton, we discuss different possible strategies
to detect new physics events as anomalies. The main goal of...

99. Calorimeter Simulation Challenge Proposal

David Shih (Rutgers University)

7/7/21, 9:00 PM