7 papers
RINO: Renormalization Group Distillation with No Labels
Zichun Hao, Raghav Kansal, Abhijith Gandrakota +6
Supervised machine learning in high-energy physics (HEP) requires training on labeled simulations of particle collisions, which are known to be unfaithful to the underlying physics…
Conditional Capacity and Routing in Mixture-of-Experts Particle Transformers
Kaushik Pendiyala, Haris Zia, Trevin Lee +8
Mixture-of-Experts (MoE) models can increase parameter capacity without proportionally increasing active computation, but it is unclear how this trade-off behaves in particle-physi…
Patch Hierarchical Attention Transformer for Efficient Particle Jet Tagging
Aaron Wang, Zihan Zhao, Alan Xia +5
Real-time jet tagging is critical for identifying short-lived particle decays in the high-throughput detectors of the Large Hadron Collider, where real-time trigger systems respons…
Why Is Attention Sparse In Particle Transformer?
Timothy Legge, Aaron Wang, Jacob Ortiz +7
Transformer-based models have achieved state-of-the-art performance in jet tagging at the CERN Large Hadron Collider (LHC), with the Particle Transformer (ParT) representing a lead…
Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging
Aaron Wang, Zihan Zhao, Subash Katel +6
Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deployment challenges in high-data-throughp…
Learning Symmetry-Independent Jet Representations via Jet-Based Joint Embedding Predictive Architecture
Subash Katel, Haoyang Li, Zihan Zhao +3
In high energy physics, self-supervised learning (SSL) methods have the potential to aid in the creation of machine learning models without the need for labeled datasets for a vari…
Large-Scale Pretraining and Finetuning for Efficient Jet Classification in Particle Physics
Zihan Zhao, Farouk Mokhtar, Raghav Kansal +2
This study introduces an innovative approach to analyzing unlabeled data in high-energy physics (HEP) through the application of self-supervised learning (SSL). Faced with the incr…