Zobrazeno 1 - 10
of 1 246
pro vyhledávání: '"Santos Fernando P."'
Autor:
Szłapczyńska Joanna, Vettor Roberto, Szłapczyński Rafał, Łącki Mirosław, Życzkowski Marcin, Hinostroza Miguel A., Santos Fernando P., Tycholiz Wojciech, Soares C. Guedes
Publikováno v:
Polish Maritime Research, Vol 29, Iss 2, Pp 87-95 (2022)
This paper describes the architecture of a weather routing system consisting of two key elements: onboard monitoring and route optimiser sub-systems. The former is responsible for collecting various onboard measurements, such as current ship position
Externí odkaz:
https://doaj.org/article/16200635c6ed4165be349dc5005b7eb5
Autor:
Michailidis, Dimitris, Röpke, Willem, Roijers, Diederik M., Ghebreab, Sennay, Santos, Fernando P.
Multi-Objective Reinforcement Learning (MORL) aims to learn a set of policies that optimize trade-offs between multiple, often conflicting objectives. MORL is computationally more complex than single-objective RL, particularly as the number of object
Externí odkaz:
http://arxiv.org/abs/2411.18195
We apply the phenomenological renormalization group to resting-state fMRI time series of brain activity in a large population. By recursively coarse-graining the data, we compute scaling exponents for the series variance, log probability of silence,
Externí odkaz:
http://arxiv.org/abs/2411.09098
Autor:
Bioucas, Francisco E. B., Queirós, Carla S. G. P., Lozano-Martín, Daniel, Ferreira, M. S., Paredes, Xavier, Santos, Ângela F., Santos, Fernando J. V., Lopes, Manuel L. M., Lampreia, Isabel M. S., Lourenço, Maria José V., de Castro, Carlos A. Nieto, Massonne, Klemens
Publikováno v:
Ind. Eng. Chem. Res. 2022, 61, 5, 2280-2305
Ionic liquids have proved to be excellent heat transfer fluids and alternatives to common HTFs used in industries for heat exchangers and other heat transfer equipment. However, its industrial utilization depends on the cost per kg of its production,
Externí odkaz:
http://arxiv.org/abs/2409.04070
Autor:
Iurada, Leonardo, Cavagnero, Niccolò, Santos, Fernando Fernandes Dos, Averta, Giuseppe, Rech, Paolo, Tommasi, Tatiana
Deep learning models are crucial for autonomous vehicle perception, but their reliability is challenged by algorithmic limitations and hardware faults. We address the latter by examining fault-tolerance in semantic segmentation models. Using establis
Externí odkaz:
http://arxiv.org/abs/2408.16952
Autor:
Lopes, Alexandre, Santos, Fernando Pereira dos, de Oliveira, Diulhio, Schiezaro, Mauricio, Pedrini, Helio
Publikováno v:
Computers & Graphics, Volume 123, October 2024, 104015
Deep neural networks have consistently represented the state of the art in most computer vision problems. In these scenarios, larger and more complex models have demonstrated superior performance to smaller architectures, especially when trained with
Externí odkaz:
http://arxiv.org/abs/2408.08250
Autor:
Góis, António, Mofakhami, Mehrnaz, Santos, Fernando P., Gidel, Gauthier, Lacoste-Julien, Simon
Agents often have individual goals which depend on a group's actions. If agents trust a forecast of collective action and adapt strategically, such prediction can influence outcomes non-trivially, resulting in a form of performative prediction. This
Externí odkaz:
http://arxiv.org/abs/2408.05146
Autor:
Smit, Martin, Santos, Fernando P.
Publikováno v:
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence Main Track (2024). Pages 220-228
Altruistic cooperation is costly yet socially desirable. As a result, agents struggle to learn cooperative policies through independent reinforcement learning (RL). Indirect reciprocity, where agents consider their interaction partner's reputation, h
Externí odkaz:
http://arxiv.org/abs/2408.04549
Topological Data Analysis (TDA) is increasingly crucial in investigating the shape of complex data structures across scientific fields, particularly in neuroscience and finance. This study delves into persistent homology, a TDA component initially ai
Externí odkaz:
http://arxiv.org/abs/2311.17912
Autor:
Vasconcelos, Vítor V., Marquitti, Flávia M. D., Ong, Theresa, McManus, Lisa C., Aguiar, Marcus, Campos, Amanda B., Dutta, Partha S., Jovanelly, Kristen, Junquera, Victoria, Kong, Jude, Krueger, Elisabeth H., Levin, Simon A., Liao, Wenying, Lu, Mingzhen, Mittal, Dhruv, Pascual, Mercedes, Pinheiro, Flávio L., Rocha, Juan, Santos, Fernando P., Sloot, Peter, Chenyang, Su, Taylor, Benton, Tekwa, Eden, Terpstra, Sjoerd, Tilman, Andrew R., Watson, James R., Yang, Luojun, Yitbarek, Senay, Zhan, Qi
Complex adaptive systems (CASs), from ecosystems to economies, are open systems and inherently dependent on external conditions. While a system can transition from one state to another based on the magnitude of change in external conditions, the rate
Externí odkaz:
http://arxiv.org/abs/2309.07449