4 papers
Continual Learning via Ensemble-Based Depth-Wise Masked Autoencoders for Data Quality Monitoring in High-Energy Physics
Dale Julson, Eric Reinhardt, Andrii Krutsylo +5
Machine learning (ML) techniques have been demonstrated to improve the accuracy and efficiency of anomaly detection (AD) when compared to conventional methods. This has led to the…
Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics
Tony Menzo, Alexander Roman, George T. Fleming +3
We present Diagrammatica, a symbolic computation extension to the HEPTAPOD agentic framework, which enables LLM agents to plan and execute multi-step theoretical calculations. Symb…
GNN For Muon Particle Momentum estimation
Vishak K Bhat, Eric A. F. Reinhardt, Sergei Gleyzer
Due to a high rate of overall data generation relative to data generation of interest, the CMS experiment at the Large Hadron Collider uses a combination of hardware- and software-…
AI Agents for Variational Quantum Circuit Design
Marco Knipfer, Alexander Roman, Konstantin T. Matchev +2
Variational quantum circuits (VQCs) constitute a central building block of near-term quantum machine learning (QML), yet the principled design of expressive and trainable architect…