Search Results for author: Abhijith Gandrakota

Found 6 papers, 3 papers with code

Interpreting Transformers for Jet Tagging

1 code implementation4 Dec 2024 Aaron Wang, Abhijith Gandrakota, Jennifer Ngadiuba, Vivekanand Sahu, Priyansh Bhatnagar, Elham E Khoda, Javier Duarte

Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC.

Jet Tagging

Real-time Anomaly Detection at the L1 Trigger of CMS Experiment

no code implementations29 Nov 2024 Abhijith Gandrakota

We present the preparation, deployment, and testing of an autoencoder trained for unbiased detection of new physics signatures in the CMS experiment Global Trigger (GT) test crate FPGAs during LHC Run 3.

Anomaly Detection

Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder

1 code implementation28 Nov 2023 Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant

Model-agnostic anomaly detection is one of the promising approaches in the search for new beyond the standard model physics.

Anomaly Detection

Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation

1 code implementation23 Nov 2023 Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant

The challenging environment of real-time data processing systems at the Large Hadron Collider (LHC) strictly limits the computational complexity of algorithms that can be deployed.

Inductive Bias Jet Tagging +1

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