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Accettura, Carlotta, Adrian, Simon, Agarwal, Rohit, Ahdida, Claudia, Aimé, Chiara, Aksoy, Avni, Alberghi, Gian Luigi, Alden, Siobhan, Alfonso, Luca, Amapane, Nicola, Amorim, David, Andreetto, Paolo, Anulli, Fabio, Appleby, Rob, Apresyan, Artur, Asadi, Pouya, Mahmoud, Mohammed Attia, Auchmann, Bernhard, Back, John, Badea, Anthony, Bae, Kyu Jung, Bahng, E. J., Balconi, Lorenzo, Balli, Fabrice, Bandiera, Laura, Barbagallo, Carmelo, Barlow, Roger, Bartoli, Camilla, Bartosik, Nazar, Barzi, Emanuela, Batsch, Fabian, Bauce, Matteo, Begel, Michael, Berg, J. Scott, Bersani, Andrea, Bertarelli, Alessandro, Bertinelli, Francesco, Bertolin, Alessandro, Bhat, Pushpalatha, Bianchi, Clarissa, Bianco, Michele, Bishop, William, Black, Kevin, Boattini, Fulvio, Bogacz, Alex, Bonesini, Maurizio, Bordini, Bernardo, de Sousa, Patricia Borges, Bottaro, Salvatore, Bottura, Luca, Boyd, Steven, Breschi, Marco, Broggi, Francesco, Brunoldi, Matteo, Buffat, Xavier, Buonincontri, Laura, Burrows, Philip Nicholas, Burt, Graeme Campbell, Buttazzo, Dario, Caiffi, Barbara, Calatroni, Sergio, Calviani, Marco, Calzaferri, Simone, Calzolari, Daniele, Cantone, Claudio, Capdevilla, Rodolfo, Carli, Christian, Carrelli, Carlo, Casaburo, Fausto, Casarsa, Massimo, Castelli, Luca, Catanesi, Maria Gabriella, Cavallucci, Lorenzo, Cavoto, Gianluca, Celiberto, Francesco Giovanni, Celona, Luigi, Cemmi, Alessia, Ceravolo, Sergio, Cerri, Alessandro, Cerutti, Francesco, Cesarini, Gianmario, Cesarotti, Cari, Chancé, Antoine, Charitonidis, Nikolaos, Chiesa, Mauro, Chiggiato, Paolo, Ciccarella, Vittoria Ludovica, Puviani, Pietro Cioli, Colaleo, Anna, Colao, Francesco, Collamati, Francesco, Costa, Marco, Craig, Nathaniel, Curtin, David, Damerau, Heiko, Da Molin, Giacomo, D'Angelo, Laura, Dasu, Sridhara, de Blas, Jorge, De Curtis, Stefania, De Gersem, Herbert, Delahaye, Jean-Pierre, Del Moro, Tommaso, Denisov, Dmitri, Denizli, Haluk, Dermisek, Radovan, Valdor, Paula Desiré, Desponds, Charlotte, Di Luzio, Luca, Di Meco, Elisa, Diociaiuti, Eleonora, Di Petrillo, Karri Folan, Di Sarcina, Ilaria, Dorigo, Tommaso, Dreimanis, Karlis, Pree, Tristan du, Yildiz, Hatice Duran, Edgecock, Thomas, Fabbri, Siara, Fabbrichesi, Marco, Farinon, Stefania, Ferrand, Guillaume, Somoza, Jose Antonio Ferreira, Fieg, Max, Filthaut, Frank, Fox, Patrick, Franceschini, Roberto, Ximenes, Rui Franqueira, Gallinaro, Michele, Garcia-Sciveres, Maurice, Garcia-Tabares, Luis, Gargiulo, Ruben, Garion, Cedric, Garzelli, Maria Vittoria, Gast, Marco, Generoso, Lisa, Gerber, Cecilia E., Giambastiani, Luca, Gianelle, Alessio, Gianfelice-Wendt, Eliana, Gibson, Stephen, Gilardoni, Simone, Giove, Dario Augusto, Giovinco, Valentina, Giraldin, Carlo, Glioti, Alfredo, Gorzawski, Arkadiusz, Greco, Mario, Grojean, Christophe, Grudiev, Alexej, Gschwendtner, Edda, Gueli, Emanuele, Guilhaudin, Nicolas, Han, Chengcheng, Han, Tao, Hauptman, John Michael, Herndon, Matthew, Hillier, Adrian D, Hillman, Micah, Holmes, Tova Ray, Homiller, Samuel, Jana, Sudip, Jindariani, Sergo, Johannesson, Sofia, Johnson, Benjamin, Jones, Owain Rhodri, Jurj, Paul-Bogdan, Kahn, Yonatan, Kamath, Rohan, Kario, Anna, Karpov, Ivan, Kelliher, David, Kilian, Wolfgang, Kitano, Ryuichiro, Kling, Felix, Kolehmainen, Antti, Kong, K. 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This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given t
Externí odkaz:
http://arxiv.org/abs/2411.02966
Graph Neural Networks Uncover Geometric Neural Representations in Reinforcement-Based Motor Learning
Graph Neural Networks (GNN) can capture the geometric properties of neural representations in EEG data. Here we utilise those to study how reinforcement-based motor learning affects neural activity patterns during motor planning, leveraging the inher
Externí odkaz:
http://arxiv.org/abs/2410.23812
We prove that $(a)$ any finitely smooth axially symmetric strictly convex domain, with everywhere positive curvature and sufficiently close to an ellipse, and $(b)$ any finitely smooth centrally symmetric strictly convex domain, even-rationally integ
Externí odkaz:
http://arxiv.org/abs/2410.12644
We comprehensively study weighted projective Reed-Muller (WPRM) codes on weighted projective planes $\mathbb{P}(1,a,b)$. We provide the universal Gr\"obner basis for the vanishing ideal of the set $Y$ of $\mathbb{F}_q$--rational points of $\mathbb{P}
Externí odkaz:
http://arxiv.org/abs/2410.11968
Nucleophobic axion models, wherein axion couplings to both protons and neutrons are simultaneously suppressed, can relax the stringent constraints from SN 1987A. However, it remains uncertain whether these models maintain their nucleophobic property
Externí odkaz:
http://arxiv.org/abs/2410.04613
Autor:
Nardi, Davide, Lamon, Edoardo, Beber, Luca, Fontanelli, Daniele, Saveriano, Matteo, Palopoli, Luigi
The introduction of artificial intelligence and robotics in telehealth is enabling personalised treatment and supporting teleoperated procedures such as lung ultrasound, which has gained attention during the COVID-19 pandemic. Although fully autonomo
Externí odkaz:
http://arxiv.org/abs/2409.17395
Autor:
Nardi, Alfonso, Morandi, Andrea, Pierrat, Romain, Goetschy, Arthur, Li, Xuanchen, Scheffold, Frank, Grange, Rachel
Nonlinear disordered media uniquely combine multiple scattering and second-harmonic generation. Here, we investigate the statistical properties of the nonlinear light generated within such media. We report super-Rayleigh statistics of the second-harm
Externí odkaz:
http://arxiv.org/abs/2409.05488
Autor:
Argenziano, Francesco, Brienza, Michele, Suriani, Vincenzo, Nardi, Daniele, Bloisi, Domenico D.
Task planning for robots in real-life settings presents significant challenges. These challenges stem from three primary issues: the difficulty in identifying grounded sequences of steps to achieve a goal; the lack of a standardized mapping between h
Externí odkaz:
http://arxiv.org/abs/2408.17379
Autor:
Hashemipour-Nazari, Marzieh, Nardi-Dei, Andrea, Goossens, Kees, Balatsoukas-Stimming, Alexios
This paper presents the hardware implementation of two variants of projection-aggregation-based decoding of Reed-Muller (RM) codes, namely unique projection aggregation (UPA) and collapsed projection aggregation (CPA). Our study focuses on introducin
Externí odkaz:
http://arxiv.org/abs/2408.10850
Federated Learning (FL) is a pivotal approach in decentralized machine learning, especially when data privacy is crucial and direct data sharing is impractical. While FL is typically associated with supervised learning, its potential in unsupervised
Externí odkaz:
http://arxiv.org/abs/2408.10664