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Emergent Properties of Finetuned Language Representation Models

Oct 23, 2019
Alexandre Matton, Luke de Oliveira

* 7 pages 

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Repurposing Decoder-Transformer Language Models for Abstractive Summarization

Sep 01, 2019
Luke de Oliveira, Alfredo Láinez Rodrigo


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CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks

Dec 21, 2017
Michela Paganini, Luke de Oliveira, Benjamin Nachman

* Phys. Rev. D 97, 014021 (2018) 
* 14 pages, 4 tables, 13 figures; version accepted by Physical Review D (PRD) 

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Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters

Dec 21, 2017
Michela Paganini, Luke de Oliveira, Benjamin Nachman

* Phys. Rev. Lett. 120, 042003 (2018) 
* 6 pages, 3 figures; version accepted by Physical Review Letters (PRL) 

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Controlling Physical Attributes in GAN-Accelerated Simulation of Electromagnetic Calorimeters

Nov 23, 2017
Luke de Oliveira, Michela Paganini, Benjamin Nachman

* 7 pages, 5 figures, in proceedings of the 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2017) 

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Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis

Jun 13, 2017
Luke de Oliveira, Michela Paganini, Benjamin Nachman

* Comput Softw Big Sci (2017) 1: 4 
* 23 pages, 23 figures, 1 table, and appendix; Added new validation metric, acknowledgements, minor corrections 

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Jet-Images -- Deep Learning Edition

Jan 22, 2017
Luke de Oliveira, Michael Kagan, Lester Mackey, Benjamin Nachman, Ariel Schwartzman

* JHEP 07 (2016) 069 
* 32 pages, 24 figures. Version that is published in JHEP 

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