LHC physics dataset for unsupervised New Physics detection at 40 MHz

Article Physics, Multidisciplinary

Adversarially Learned Anomaly Detection on CMS open data: re-discovering the top quark

O. Knapp et al.

Summary: The study applies the ALAD algorithm to detect new physics processes in proton-proton collisions at the Large Hadron Collider, achieving performances comparable to Variational Autoencoders and substantial improvement in some cases. Training the ALAD algorithm on 4.4 fb-1 of 8 TeV CMS Open Data, the study demonstrates a data-driven anomaly detection and characterization in real life, rediscovering the top quark at the LHC.

EUROPEAN PHYSICAL JOURNAL PLUS (2021)

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Article Computer Science, Artificial Intelligence

Fast convolutional neural networks on FPGAs with hls4ml

Thea Aarrestad et al.

Summary: An automated tool is introduced for deploying ultra low-latency, low-power deep neural networks with convolutional layers on FPGAs. Through model compression techniques, significant reduction in FPGA critical resource consumption can be achieved with minimal to no loss in model accuracy.

MACHINE LEARNING-SCIENCE AND TECHNOLOGY (2021)

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Article Computer Science, Artificial Intelligence

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

Claudionor N. Coelho et al.

Summary: The paper discusses a quantization method for deep learning models that can reduce energy consumption and model size while maintaining high accuracy, suitable for efficient inference on edge devices.

NATURE MACHINE INTELLIGENCE (2021)

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Review Physics, Multidisciplinary