Följ
Luke de Oliveira
Titel
Citeras av
Citeras av
År
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
4202016
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
3782018
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
3062017
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
2662018
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
362020
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
362016
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
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
Language model for abstractive summarization
LP De Oliveira, AL Rodrigo
US Patent 11,475,210, 2022
62022
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
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
Transition-driven search
LP De Oliveira, U Akeel, AL Rodrigo, NA Amador, S Kumar, LB Dremer, ...
US Patent App. 17/305,976, 2022
32022
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
32022
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 App. 17/939,176, 2022
22022
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
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20