Calorimeter shower simulation is a major bottleneck in the Large Hadron
...
Simulating particle detector response is the single most expensive step ...
Large-scale astrophysics datasets present an opportunity for new machine...
Choosing which properties of the data to use as input to multivariate
de...
CaloFlow is a new and promising approach to fast calorimeter simulation ...
The computational cost for high energy physics detector simulation in fu...
Machine learning plays a crucial role in enhancing and accelerating the
...
There is a growing need for anomaly detection methods that can broaden t...
Recently, we introduced CaloFlow, a high-fidelity generative model for G...
The identification of anomalous overdensities in data - group or collect...
We introduce CaloFlow, a fast detector simulation framework based on
nor...
Anomaly detection techniques are growing in importance at the Large Hadr...
Significant advances in deep learning have led to more widely used and
p...
Given the lack of evidence for new particle discoveries at the Large Had...
We leverage recent breakthroughs in neural density estimation to propose...