28 citations · 51 across the 8 of their papers we have counts for
3 papers · 1 filter
Chopping and distilling variational autoencoders for real-time anomaly detection in high energy physics
Max Cohen, Rajat Gupta, Sterre Hoogendoorn +3
Anomaly detection (AD) has recently emerged as an exciting alternative to conventional search strategies in high energy physics using artificial intelligence (AI) and machine learn…
Memristive tabular variational autoencoder for compression of analog data in high energy physics
Rajat Gupta, Yuvaraj Elangovan, Tae Min Hong +5
We present an implementation of edge AI to compress data on an in-memory analog content-addressable memory (ACAM) device. A variational autoencoder is trained on a simulated sample…
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jennifer Ott, Jenni Ott +129
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…