| |
Author |
Title |
Year |
Publication  |
Volume |
Pages |
Links |
|
|
Lee, H.M.; Park, M.; Sanz, V. |
Gravity-Mediated Dark Matter at a low reheating temperature |
2025 |
Journal of High Energy Physics |
05 |
126 - 26pp |
|
|
|
Mantani, L.; Sanz, V. |
Probing the flavour-blind SMEFT: EFT validity and the interplay of energy scales |
2025 |
Journal of High Energy Physics |
06 |
147 - 31pp |
|
|
|
Butterworth, J.; Cullingworth, M.; Egan, J.; Esser, F.; Sanz, V.; Ubiali, M. |
Probing the coupling of axions to tops and gluons with LHC measurements |
2026 |
Journal of High Energy Physics |
02 |
073 - 28pp |
|
|
|
Bendavid, J.; Conde, D.; Morales-Alvarado, M.; Sanz, V.; Ubiali, M. |
Angular coefficients from interpretable machine learning with symbolic regression |
2026 |
Journal of High Energy Physics |
02 |
081 - 43pp |
|
|
|
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 |
|
|
|
Barenboim, G.; Del Debbio, L.; Hirn, J.; Sanz, V. |
Exploring how a generative AI interprets music |
2024 |
Neural Computing and Applications |
36 |
17007–17022 |
|
|
|
Huang, F.; Sanz, V.; Shu, J.; Xue, X. |
LIGO as a probe of dark sectors |
2021 |
Physical Review D |
104 |
095001 - 9pp |
|
|
|
Sanchis-Lozano, M.A.; Sanz, V. |
Observable imprints of primordial gravitational waves on the temperature anisotropies of the cosmic microwave background |
2024 |
Physical Review D |
109 |
063529 - 11pp |
|
|
|
Hirsch, M.; Mantani, L.; Sanz, V. |
Data-Driven Discovery Strategy for Standard Model Effective Field Theory Searches |
2025 |
Physical Review Letters |
135 |
241801 - 8pp |
|
