| ESPNN: A novel electronic stopping power neural-network code built on the IAEA stopping power database. I. Atomic targets F Bivort Haiek, AMP Mendez, CC Montanari, DM Mitnik Journal of Applied Physics 132 (24), 2022 | 12 | 2022 |
| The IAEA electronic stopping power database: Modernization, review, and analysis of the existing experimental data CC Montanari, P Dimitriou, L Marian, AMP Mendez, JP Peralta, ... Nuclear Instruments and Methods in Physics Research Section B: Beam …, 2024 | 3 | 2024 |
| Interactive grounded language understanding in a collaborative environment: Retrospective on iglu 2022 competition J Kiseleva, A Skrynnik, A Zholus, S Mohanty, N Arabzadeh, MA Côté, ... NeurIPS 2022 Competition Track, 204-216, 2023 | 2 | 2023 |
| Electronic stopping power: the IAEA database and state of the art experimental knowledge CC Montanari, F Bivort-Haiek, P Dimitriou, L Marian, AMP Mendez, ... arXiv preprint arXiv:2402.03080, 2024 | | 2024 |
| Machine learning for modeling the electronic stopping power of ions F Bivort Haiek, A Mendez, C Montanari, D Mitnik APS Annual Gaseous Electronics Meeting Abstracts, FW1. 001, 2023 | | 2023 |
| ESPNN: Deep Neural Network on the IAEA stopping power database. Atomic targets F Bivort Haiek, A Mendez, C Montanari, D Mitnik https://arxiv.org/abs/2210.10950, 2022 | | 2022 |
| Redes complejas y el problema de reposicionamiento de reposicionamiento de fármacos F Bivort Haiek | | 2017 |
| Redes complejas y el problema de reposicionamiento de fármacos F Bivort Haiek Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales, 2017 | | 2017 |
