| |
Author  |
Title |
Year |
Publication |
Volume |
Pages |
Links |
|
|
Escudero, M.; Rius, N.; Sanz, V. |
Sterile neutrino portal to Dark Matter I: the U(1)(B-L) case |
2017 |
Journal of High Energy Physics |
02 |
045 - 27pp |
|
|
|
Esser, F.; Madigan, M.; Sanz, V.; Ubiali, M. |
On the coupling of axion-like particles to the top quark |
2023 |
Journal of High Energy Physics |
09 |
063 - 39pp |
|
|
|
Folgado, M.G.; Sanz, V. |
Exploring the political pulse of a country using data science tools |
2022 |
Journal of Computational Social Science |
5 |
987-1000 |
|
|
|
Folgado, M.G.; Sanz, V. |
On the Interpretation of Nonresonant Phenomena at Colliders |
2021 |
Advances in High Energy Physics |
2021 |
2573471 - 12pp |
|
|
|
Garcia Navarro, J.E.; Fernandez-Prieto, L.M.; Villaseñor, A.; Sanz, V.; Ammirati, J.B.; Diaz Suarez, E.A.; Garcia, C. |
Performance of Deep Learning Pickers in Routine Network Processing Applications |
2022 |
Seismological Research Letters |
93 |
2529-2542 |
|
|
|
Gomez Ambrosio, R.; ter Hoeve, J.; Madigan, M.; Rojo, J.; Sanz, V. |
Unbinned multivariate observables for global SMEFT analyses from machine learning |
2023 |
Journal of High Energy Physics |
03 |
033 - 66pp |
|
|
|
Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. |
A deep Generative Artificial Intelligence system to predict species coexistence patterns |
2022 |
Methods in Ecology and Evolution |
13 |
1052-1061 |
|
|
|
Huang, F.; Sanz, V.; Shu, J.; Xue, X. |
LIGO as a probe of dark sectors |
2021 |
Physical Review D |
104 |
095001 - 9pp |
|
|
|
Kasieczka, G. et al; Sanz, V. |
The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics |
2021 |
Reports on Progress in Physics |
84 |
124201 - 64pp |
|
|
|
Khosa, C.K.; Mars, L.; Richards, J.; Sanz, V. |
Convolutional neural networks for direct detection of dark matter |
2020 |
Journal of Physics G |
47 |
095201 - 20pp |
|
