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Benjamin Nachman

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Designing Observables for Measurements with Deep Learning

Oct 12, 2023
Owen Long, Benjamin Nachman

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The Optimal use of Segmentation for Sampling Calorimeters

Oct 02, 2023
Fernando Torales Acosta, Bishnu Karki, Piyush Karande, Aaron Angerami, Miguel Arratia, Kenneth Barish, Ryan Milton, Sebastián Morán, Benjamin Nachman, Anshuman Sinha

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Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation

Sep 12, 2023
Tobias Golling, Samuel Klein, Radha Mastandrea, Benjamin Nachman, John Andrew Raine

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Improving Generative Model-based Unfolding with Schrödinger Bridges

Aug 23, 2023
Sascha Diefenbacher, Guan-Horng Liu, Vinicius Mikuni, Benjamin Nachman, Weili Nie

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Comparison of Point Cloud and Image-based Models for Calorimeter Fast Simulation

Jul 31, 2023
Fernando Torales Acosta, Vinicius Mikuni, Benjamin Nachman, Miguel Arratia, Bishnu Karki, Ryan Milton, Piyush Karande, Aaron Angerami

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High-dimensional and Permutation Invariant Anomaly Detection

Jun 06, 2023
Vinicius Mikuni, Benjamin Nachman

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Learning Likelihood Ratios with Neural Network Classifiers

May 17, 2023
Shahzar Rizvi, Mariel Pettee, Benjamin Nachman

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ELSA -- Enhanced latent spaces for improved collider simulations

May 12, 2023
Benjamin Nachman, Ramon Winterhalder

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Weakly-Supervised Anomaly Detection in the Milky Way

May 05, 2023
Mariel Pettee, Sowmya Thanvantri, Benjamin Nachman, David Shih, Matthew R. Buckley, Jack H. Collins

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