Add to ORKGWe present a new algorithm for anomaly detection called Anomaly Awareness. The algorithm learns about normal events while being made aware of the anomalies through a modification of the cost function. We show how this method works in different Particle Physics situations and in standard Computer Vision tasks. For example, we apply the method to images from a Fat Jet topology generated by Standard Model Top and QCD events, and test it against an array of new physics scenarios, including Higgs production with EFT effects and resonances decaying into two, three or four subjets. We find that the algorithm is effective identifying anomalies not seen before, and becomes robust as we make it aware of a varied-enough set of anomalies.Comment: 12 pa...
Anomaly detection aims at identifying data points that show systematic deviations from the majority ...
Recently, the concept of weakly supervised learning has gained popularity in the high-energy physics...
Much hope for finding new physics phenomena at microscopic scale relies on the observations obtained...
This paper discusses model-agnostic searches for new physics at the Large Hadron Collider (LHC) usin...
Anomaly detection with convolutional autoencoders is a popular method to search for new physics in a...
Anomaly detection has been considered under several extents of prior knowledge. Unsupervised methods...
Experiments at particle colliders are the primary source of insight into physics at microscopic scal...
We investigate a method of model-agnostic anomaly detection through studying jets, collimated sprays...
In this paper we propose a new strategy, based on anomaly detection methods, to search for new physi...
Recent experimental searches for particles beyond the Standard Model (BSM) have yielded little in th...
There is a growing need for machine learning-based anomaly detection strategies to broaden the searc...
Anomaly detection is the task of identifying observations in a dataset that do not conform the expec...
There is a growing need for machine learning-based anomaly detection strategies to broaden the searc...
The concept of statistical anomalies, or outliers, has fascinated experimentalists since the earlies...
The concept of statistical anomalies, or outliers, has fascinated experimentalists since the earlies...
Anomaly detection aims at identifying data points that show systematic deviations from the majority ...
Recently, the concept of weakly supervised learning has gained popularity in the high-energy physics...
Much hope for finding new physics phenomena at microscopic scale relies on the observations obtained...
This paper discusses model-agnostic searches for new physics at the Large Hadron Collider (LHC) usin...
Anomaly detection with convolutional autoencoders is a popular method to search for new physics in a...
Anomaly detection has been considered under several extents of prior knowledge. Unsupervised methods...
Experiments at particle colliders are the primary source of insight into physics at microscopic scal...
We investigate a method of model-agnostic anomaly detection through studying jets, collimated sprays...
In this paper we propose a new strategy, based on anomaly detection methods, to search for new physi...
Recent experimental searches for particles beyond the Standard Model (BSM) have yielded little in th...
There is a growing need for machine learning-based anomaly detection strategies to broaden the searc...
Anomaly detection is the task of identifying observations in a dataset that do not conform the expec...
There is a growing need for machine learning-based anomaly detection strategies to broaden the searc...
The concept of statistical anomalies, or outliers, has fascinated experimentalists since the earlies...
The concept of statistical anomalies, or outliers, has fascinated experimentalists since the earlies...
Anomaly detection aims at identifying data points that show systematic deviations from the majority ...
Recently, the concept of weakly supervised learning has gained popularity in the high-energy physics...
Much hope for finding new physics phenomena at microscopic scale relies on the observations obtained...