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Luke de Oliveira
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Jet-images—deep learning edition
L de Oliveira, M Kagan, L Mackey, B Nachman, A Schwartzman
Journal of High Energy Physics 2016 (7), 1-32, 2016
4212016
CaloGAN: Simulating 3D high energy particle showers in multilayer electromagnetic calorimeters with generative adversarial networks
M Paganini, L de Oliveira, B Nachman
Physical Review D 97 (1), 014021, 2018
3802018
Learning particle physics by example: location-aware generative adversarial networks for physics synthesis
L de Oliveira, M Paganini, B Nachman
Computing and Software for Big Science 1 (1), 4, 2017
3072017
Accelerating science with generative adversarial networks: an application to 3D particle showers in multilayer calorimeters
M Paganini, L de Oliveira, B Nachman
Physical review letters 120 (4), 042003, 2018
2682018
Controlling physical attributes in GAN-accelerated simulation of electromagnetic calorimeters
L De Oliveira, M Paganini, B Nachman
Journal of Physics: Conference Series 1085 (4), 042017, 2018
622018
Electromagnetic showers beyond shower shapes
L De Oliveira, B Nachman, M Paganini
Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 2020
372020
Image Processing, Computer Vision, and Deep Learning: new approaches to the analysis and physics interpretation of LHC events
A Schwartzman, M Kagan, L Mackey, B Nachman, L De Oliveira
Journal of Physics: Conference Series 762 (1), 012035, 2016
372016
Humor detection in yelp reviews
L De Oliveira, AL Rodrigo
Retrieved on December 15, 2019, 2015
232015
Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis, Comput. Softw. Big Sci. 1 (2017) 1, 4
L de Oliveira, M Paganini, B Nachman
arXiv preprint arXiv:1701.05927, 0
16
Language model for abstractive summarization
LP De Oliveira, AL Rodrigo
US Patent 11,475,210, 2022
72022
Boosted jet tagging with jet-images and deep neural networks
M Kagan, L de Oliveira, L Mackey, B Nachman, A Schwartzman
EPJ Web of Conferences 127, 00009, 2016
72016
HEP Software Foundation Community White Paper Working Group-Detector Simulation
HEP Foundation, J Apostolakis, M Asai, S Banerjee, R Bianchi, P Canal, ...
arXiv preprint arXiv:1803.04165, 2018
5*2018
Tips and tricks for training GANs with physics constraints
L de Oliveira, M Paganini, B Nachman
Proceedings of the Deep Learning for Physical Sciences Workshop at NIPS, 2017
52017
CodeDroid: a framework to develop context-aware applications
L de Oliveira, A Loureiro
The Fourth International Conferences on Advances in Human-oriented and …, 2011
52011
Transition-driven search
LP De Oliveira, U Akeel, AL Rodrigo, NA Amador, S Kumar, LB Dremer, ...
US Patent App. 17/305,976, 2022
42022
Tool for categorizing and extracting data from audio conversations
AL Rodrigo, T Cole, U Akeel, LP De Oliveira
US Patent App. 17/449,405, 2022
42022
Survey of machine learning techniques for high energy electromagnetic shower classification
M Paganini, L de Oliveira, B Nachman
Deep Learning for Physical Sciences Workshop at the 31st Conference on …, 2017
42017
Repurposing decoder-transformer language models for abstractive summarization
L de Oliveira, AL Rodrigo
arXiv preprint arXiv:1909.00325, 2019
32019
Language model for abstractive summarization
LP De Oliveira, AL Rodrigo
US Patent 11,941,348, 2024
22024
Generative Models for Fast Simulation
M Paganini, L de Oliveira, B Nachman, D Derkach, F Ratnikov, ...
Artificial Intelligence For High Energy Physics, 153-189, 2022
12022
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