744 citations · 6.5k across the 102 of their papers we have counts for
107 papers
LHC Hadronic Jet Generation Using Convolutional Variational Autoencoders with Normalizing Flows
Breno Orzari, Nadezda Chernyavskaya, Raphael Cobe +7
In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data gen…
Knowledge Distillation for Anomaly Detection
Adrian Alan Pol, Ekaterina Govorkova, Sonja Gronroos +5
Unsupervised deep learning techniques are widely used to identify anomalous behaviour. The performance of such methods is a product of the amount of training data and the model siz…
Triggering Dark Showers with Conditional Dual Auto-Encoders
Luca Anzalone, Simranjit Singh Chhibra, Benedikt Maier +2
We present a family of conditional dual auto-encoders (CoDAEs) for generic and model-independent new physics searches at colliders. New physics signals, which arise from new types…
Differentiable Earth Mover's Distance for Data Compression at the High-Luminosity LHC
Rohan Shenoy, Javier Duarte, Christian Herwig +5
The Earth mover's distance (EMD) is a useful metric for image recognition and classification, but its usual implementations are not differentiable or too slow to be used as a loss…
Goodness of fit by Neyman-Pearson testing
Gaia Grosso, Marco Letizia, Maurizio Pierini +1
The Neyman-Pearson strategy for hypothesis testing can be employed for goodness of fit if the alternative hypothesis is selected from data by exploring a rich parametrised family o…
Symbolic Regression on FPGAs for Fast Machine Learning Inference
Ho Fung Tsoi, Adrian Alan Pol, Vladimir Loncar +7
The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to enhance physics sensitiv…