Search Results for author:
Found 4 papers, 1 papers with code
Re-Simulation-based Self-Supervised Learning for Pre-Training Foundation Models
Self-Supervised Learning (SSL) is at the core of training modern large machine learning models, providing a scheme for learning powerful representations that can be used in a variety of downstream tasks.
Autoencoders for Real-Time SUEP Detection
A deep convolutional neural autoencoder network has been trained using QCD events by taking transverse energy deposits in the inner tracker, electromagnetic calorimeter, and hadron calorimeter sub-detectors as 3-channel image data.
Triggering Dark Showers with Conditional Dual Auto-Encoders
We present a search formulated as an anomaly detection (AD) problem, using an AE to define a criterion to decide about the physics nature of an event.
LHC Dark Matter Working Group: Next-generation spin-0 dark matter models
The exclusion limits obtained from the proposed scans can be consistently compared to the constraints on the $\textrm{2HDM+a}$ model that derive from DD, ID and the DM relic density.
High Energy Physics - Experiment High Energy Physics - Phenomenology
