531 citations · 7.1k across the 80 of their papers we have counts for
6 papers · 1 filter
ABCDisCo: Automating the ABCD Method with Machine Learning
Gregor Kasieczka, Benjamin Nachman, Matthew D. Schwartz +1
The ABCD method is one of the most widely used data-driven background estimation techniques in high energy physics. Cuts on two statistically-independent classifiers separate signa…
A Complete Framework for Tau Polarimetry in Decays
Pouya Asadi, Anna Hallin, Jorge Martin Camalich +2
The meson decays and are sensitive probes of the transition. In this work we present a complete framework to obtain the maximum information on t…
Strange Jet Tagging
Yuichiro Nakai, David Shih, Scott Thomas
Tagging jets of strongly interacting particles initiated by energetic strange quarks is one of the few largely unexplored Standard Model object classification problems remaining in…
Simulation Assisted Likelihood-free Anomaly Detection
Anders Andreassen, Benjamin Nachman, David Shih
Given the lack of evidence for new particle discoveries at the Large Hadron Collider (LHC), it is critical to broaden the search program. A variety of model-independent searches ha…
DisCo Fever: Robust Networks Through Distance Correlation
Gregor Kasieczka, David Shih
While deep learning has proven to be extremely successful at supervised classification tasks at the LHC and beyond, for practical applications, raw classification accuracy is often…
Anomaly Detection with Density Estimation
Benjamin Nachman, David Shih
We leverage recent breakthroughs in neural density estimation to propose a new unsupervised anomaly detection technique (ANODE). By estimating the probability density of the data i…