738 citations · 3k across the 134 of their papers we have counts for
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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…
GWAK: Gravitational-Wave Anomalous Knowledge with Recurrent Autoencoders
Ryan Raikman, Eric A. Moreno, Ekaterina Govorkova +10
Matched-filtering detection techniques for gravitational-wave (GW) signals in ground-based interferometers rely on having well-modeled templates of the GW emission. Such techniques…
Applications of Deep Learning to physics workflows
Manan Agarwal, Jay Alameda, Jeroen Audenaert +65
Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing…
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…