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pro vyhledávání: '"A. de Santi"'
The connection between galaxies and dark matter halos encompasses a range of processes and play a pivotal role in our understanding of galaxy formation and evolution. Traditionally, this link has been established through physical or empirical models.
Externí odkaz:
http://arxiv.org/abs/2410.17844
Autor:
Peron, Guilherme de Santi, Monteiro, Marcos Eduardo Pivaro, de Barros, João Luís Verdegay, Farhat, Jamil, Brante, Glauber
The Internet of Things (IoT) empowers small devices to sense, react, and communicate, with applications ranging from smart ordinary household objects to complex industrial processes. To provide access to an increasing number of IoT devices, particula
Externí odkaz:
http://arxiv.org/abs/2410.03383
Patch-based Intuitive Multimodal Prototypes Network (PIMPNet) for Alzheimer's Disease classification
Volumetric neuroimaging examinations like structural Magnetic Resonance Imaging (sMRI) are routinely applied to support the clinical diagnosis of dementia like Alzheimer's Disease (AD). Neuroradiologists examine 3D sMRI to detect and monitor abnormal
Externí odkaz:
http://arxiv.org/abs/2407.14277
How can a scientist use a Reinforcement Learning (RL) algorithm to design experiments over a dynamical system's state space? In the case of finite and Markovian systems, an area called Active Exploration (AE) relaxes the optimization problem of exper
Externí odkaz:
http://arxiv.org/abs/2407.13364
Global Reinforcement Learning: Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods
In classic Reinforcement Learning (RL), the agent maximizes an additive objective of the visited states, e.g., a value function. Unfortunately, objectives of this type cannot model many real-world applications such as experiment design, exploration,
Externí odkaz:
http://arxiv.org/abs/2407.09905
Autor:
De Santi, Federico, Razzano, Massimiliano, Fidecaro, Francesco, Muccillo, Luca, Papalini, Lucia, Patricelli, Barbara
A yet undetected class of GW signals is represented by the close encounters between compact objects in highly-eccentric e~1 orbits, that can occur in binary systems formed in dense environments such as globular clusters. The expected gravitational si
Externí odkaz:
http://arxiv.org/abs/2404.12028
Autor:
De Santi, Lisa Anita, Schlötterer, Jörg, Scheschenja, Michael, Wessendorf, Joel, Nauta, Meike, Positano, Vincenzo, Seifert, Christin
Information from neuroimaging examinations is increasingly used to support diagnoses of dementia, e.g., Alzheimer's disease. While current clinical practice is mainly based on visual inspection and feature engineering, Deep Learning approaches can be
Externí odkaz:
http://arxiv.org/abs/2403.18328
Autor:
S. Coiai, F. Cicogna, A. de Santi, L. Perez Amaro, R. Spiniello, F. Signori, S. Fiori, W. Oberhauser, E. Passaglia
Publikováno v:
eXPRESS Polymer Letters, Vol 11, Iss 3, Pp 163-175 (2017)
Low molecular weight polyesters were end-functionalized with ammonium and carboxylate salts and used in ionic exchange reactions with respectively cationic (MMT) and anionic (LDH) clays. The hybrid organic-inorganic substrates were structurally analy
Externí odkaz:
https://doaj.org/article/bfa86ef1bbff415d80997a8a13eadfc5
Autor:
de Santi, Natalí S. M., Villaescusa-Navarro, Francisco, Abramo, L. Raul, Shao, Helen, Perez, Lucia A., Castro, Tiago, Ni, Yueying, Lovell, Christopher C., Hernandez-Martinez, Elena, Marinacci, Federico, Spergel, David N., Dolag, Klaus, Hernquist, Lars, Vogelsberger, Mark
It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Sant
Externí odkaz:
http://arxiv.org/abs/2310.15234
Posterior sampling allows exploitation of prior knowledge on the environment's transition dynamics to improve the sample efficiency of reinforcement learning. The prior is typically specified as a class of parametric distributions, the design of whic
Externí odkaz:
http://arxiv.org/abs/2310.07518