Zobrazeno 1 - 10
of 1 349
pro vyhledávání: '"Marinazzo"'
Autor:
Mijatovic, Gorana, Antonacci, Yuri, Javorka, Michal, Marinazzo, Daniele, Stramaglia, Sebastiano, Faes, Luca
Many complex systems in science and engineering are modeled as networks whose nodes and links depict the temporal evolution of each system unit and the dynamic interaction between pairs of units, which are assessed respectively using measures of auto
Externí odkaz:
http://arxiv.org/abs/2408.15617
This paper studies emergent phenomena in neural networks by focusing on grokking where models suddenly generalize after delayed memorization. To understand this phase transition, we utilize higher-order mutual information to analyze the collective be
Externí odkaz:
http://arxiv.org/abs/2408.08944
Autor:
Luo, Xiaoliang, Rechardt, Akilles, Sun, Guangzhi, Nejad, Kevin K., Yáñez, Felipe, Yilmaz, Bati, Lee, Kangjoo, Cohen, Alexandra O., Borghesani, Valentina, Pashkov, Anton, Marinazzo, Daniele, Nicholas, Jonathan, Salatiello, Alessandro, Sucholutsky, Ilia, Minervini, Pasquale, Razavi, Sepehr, Rocca, Roberta, Yusifov, Elkhan, Okalova, Tereza, Gu, Nianlong, Ferianc, Martin, Khona, Mikail, Patil, Kaustubh R., Lee, Pui-Shee, Mata, Rui, Myers, Nicholas E., Bizley, Jennifer K, Musslick, Sebastian, Bilgin, Isil Poyraz, Niso, Guiomar, Ales, Justin M., Gaebler, Michael, Murty, N Apurva Ratan, Loued-Khenissi, Leyla, Behler, Anna, Hall, Chloe M., Dafflon, Jessica, Bao, Sherry Dongqi, Love, Bradley C.
Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could pot
Externí odkaz:
http://arxiv.org/abs/2403.03230
Transfer Entropy (TE), the primary method for determining directed information flow within a network system, can exhibit bias - either in deficiency or excess - during both pairwise and conditioned calculations, owing to high-order dependencies among
Externí odkaz:
http://arxiv.org/abs/2402.03229
Autor:
Mijatovic, Gorana, Sparacino, Laura, Antonacci, Yuri, Javorka, Michal, Marinazzo, Daniele, Stramaglia, Sebastiano, Faes, Luca
The network representation is becoming increasingly popular for the description of cardiovascular interactions based on the analysis of multiple simultaneously collected variables. However, the traditional methods to assess network links based on pai
Externí odkaz:
http://arxiv.org/abs/2401.05556
Autor:
Vega-Hernandez, Mayrim, Galan-Garcia, Lidice, Perez-Hidalgo-Gato, Jhoanna, Ontivero-Ortega, Marlis, Garcia-Agustin, Daysi, Garcia-Reyes, Ronaldo, Bosch-Bayard, Jorge, Marinazzo, Daniele, Martinez-Montes, Eduardo, Valdes-Sosa, A, Pedro
Objective: We seek stable Electrophysiological Source Imaging (ESI) biomarkers associated with Gait Speed (GS) as a measure of functional decline. Towards this end we determine the predictive value of ESI activation and connectivity patterns of resti
Externí odkaz:
http://arxiv.org/abs/2307.11273
Autor:
Sonia Montemurro, Daniel Borek, Daniele Marinazzo, Sara Zago, Fabio Masina, Ettore Napoli, Nicola Filippini, Giorgio Arcara
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Recent studies have shown a growing interest in the so-called “aperiodic” component of the EEG power spectrum, which describes the overall trend of the whole spectrum with a linear or exponential function. In the field of brain aging, th
Externí odkaz:
https://doaj.org/article/849ae34db55a489887712d7728e82f48
Autor:
Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Bollman, Steffen, Stewart, Ashley, Fischer, Jeremy, Faskowitz, Joshua, Chaumon, Maximilien, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuele, Hanson, Jamie L., Avesani, Paolo, Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., George, Nathalie, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., Pestilli, Franco
Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR
Externí odkaz:
http://arxiv.org/abs/2306.02183
Quantifying which neurons are important with respect to the classification decision of a trained neural network is essential for understanding their inner workings. Previous work primarily attributed importance to individual neurons. In this work, we
Externí odkaz:
http://arxiv.org/abs/2211.00416
Autor:
Stella, Massimo, Citraro, Salvatore, Rossetti, Giulio, Marinazzo, Daniele, Kenett, Yoed N., Vitevitch, Michael S.
The mental lexicon is a complex cognitive system representing information about the words/concepts that one knows. Decades of psychological experiments have shown that conceptual associations across multiple, interactive cognitive levels can greatly
Externí odkaz:
http://arxiv.org/abs/2210.00500