An oracle that correctly predicts the outcome of every particle physics experiment, the
products of every possible chemical reaction or the function of every protein would …

Compelling experimental evidence suggests the existence of new physics beyond the well-
established and tested standard model of particle physics. Various current and upcoming …

A new paradigm for data-driven, model-agnostic new physics searches at colliders is
emerging, and aims to leverage recent breakthroughs in anomaly detection and machine …

We propose a new model-agnostic search strategy for physics beyond the standard model
(BSM) at the LHC, based on a novel application of neural density estimation to anomaly …

This paper presents a model-agnostic search for narrow resonances in the dijet final state in
the mass range 1.8-6 TeV. The signal is assumed to produce jets with substructure atypical …

A bstract Anomaly detection relies on designing a score to determine whether a particular
event is uncharacteristic of a given background distribution. One way to define a score is to …

Autoencoders as tools behind anomaly searches at the LHC have the structural problem that
they only work in one direction, extracting jets with higher complexity but not the other way …

We show how to deal with uncertainties on the Standard Model predictions in an agnostic
new physics search strategy that exploits artificial neural networks. Our approach builds …

There is a growing need for anomaly detection methods that can broaden the search for new
particles in a model-agnostic manner. Most proposals for new methods focus exclusively on …

There is a growing need for machine-learning-based anomaly detection strategies to
broaden the search for beyond-the-Standard-Model physics at the Large Hadron Collider …