5 papers
Towards Tensor Network Models for Low-Latency Jet Tagging on FPGAs
Alberto Coppi, Ema Puljak, Lorenzo Borella +6
We present a systematic study of Tensor Network (TN) models $\unicode{x2013}$ Matrix Product States (MPS) and Tree Tensor Networks (TTN) $\unicode{x2013}$ for real-time jet tagging…
AIE4ML: An End-to-End Framework for Compiling Neural Networks for the Next Generation of AMD AI Engines
Dimitrios Danopoulos, Enrico Lupi, Chang Sun +4
Efficient AI inference on AMD's Versal AI Engine (AIE) is challenging due to tightly coupled VLIW execution, explicit datapaths, and local memory management. Prior work focused on…
Knowledge is Overrated: A zero-knowledge machine learning and cryptographic hashing-based framework for verifiable, low latency inference at the LHC
Pratik Jawahar, Caterina Doglioni, Maurizio Pierini
Low latency event-selection (trigger) algorithms are essential components of Large Hadron Collider (LHC) operation. Modern machine learning (ML) models have shown great offline per…
Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC
Ema Puljak, Maurizio Pierini, Artur Garcia-Saez
The pursuit of discovering new phenomena at the Large Hadron Collider (LHC) demands constant innovation in algorithms and technologies. Tensor networks are mathematical models on t…
tn4ml: Tensor Network Training and Customization for Machine Learning
Ema Puljak, Sergio Sanchez-Ramirez, Sergi Masot-Llima +3
Tensor Networks have emerged as a prominent alternative to neural networks for addressing Machine Learning challenges in foundational sciences, paving the way for their application…