| Author |
Title |
Year |
Publication  |
Volume |
Pages |
| Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. |
Mapping the SMEFT to discoverable models |
2022 |
Journal of High Energy Physics |
09 |
229 - 34pp |
| 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 |
| Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. |
SMEFT goes dark: Dark Matter models for four-fermion operators |
2023 |
Journal of High Energy Physics |
09 |
081 - 47pp |
| 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 |
| Lessa, A.; Sanz, V. |
Going beyond Top EFT |
2024 |
Journal of High Energy Physics |
04 |
107 - 29pp |
| Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. |
Fermionic UV models for neutral triple gauge boson vertices |
2024 |
Journal of High Energy Physics |
07 |
275 - 28pp |
| Esser, F.; Madigan, M.; Salas-Bernardez, A.; Sanz, V.; Ubiali, M. |
Di-Higgs production via axion-like particles |
2024 |
Journal of High Energy Physics |
10 |
164 - 22pp |
| Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. |
Faking ZZZ vertices at the LHC |
2024 |
Journal of High Energy Physics |
12 |
098 - 20pp |
| 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 |
| 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 |
