Search Results for author: Adrian Alan Pol

Found 9 papers, 3 papers with code

Symbolic Regression on FPGAs for Fast Machine Learning Inference

no code implementations6 May 2023 Ho Fung Tsoi, Adrian Alan Pol, Vladimir Loncar, Ekaterina Govorkova, Miles Cranmer, Sridhara Dasu, Peter Elmer, Philip Harris, Isobel Ojalvo, Maurizio Pierini

The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to enhance physics sensitivity while still meeting data processing time constraints.

Neural Architecture Search regression +1

Anomaly Detection With Conditional Variational Autoencoders

no code implementations12 Oct 2020 Adrian Alan Pol, Victor Berger, Gianluca Cerminara, Cecile Germain, Maurizio Pierini

Exploiting the rapid advances in probabilistic inference, in particular variational Bayes and variational autoencoders (VAEs), for anomaly detection (AD) tasks remains an open research question.

Anomaly Detection

Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors

3 code implementations15 Jun 2020 Claudionor N. Coelho Jr., Aki Kuusela, Shan Li, Hao Zhuang, Thea Aarrestad, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Adrian Alan Pol, Sioni Summers

Although the quest for more accurate solutions is pushing deep learning research towards larger and more complex algorithms, edge devices demand efficient inference and therefore reduction in model size, latency and energy consumption.


Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron Collider

1 code implementation27 Jul 2018 Adrian Alan Pol, Gianluca Cerminara, Cecile Germain, Maurizio Pierini, Agrima Seth

Reliable data quality monitoring is a key asset in delivering collision data suitable for physics analysis in any modern large-scale High Energy Physics experiment.

Anomaly Detection

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