Zobrazeno 1 - 10
of 3 545
pro vyhledávání: '"A P, Cossu"'
Co-based honeycomb magnets have been actively studied recently for the potential realization of emergent quantum magnetism therein such as the Kitaev spin liquid. Here we employ density functional and dynamical mean-field theory methods to examine a
Externí odkaz:
http://arxiv.org/abs/2406.18003
We develop MultiSTOP, a Reinforcement Learning framework for solving functional equations in physics. This new methodology produces actual numerical solutions instead of bounds on them. We extend the original BootSTOP algorithm by adding multiple con
Externí odkaz:
http://arxiv.org/abs/2404.14909
Continual Learning (CL) focuses on maximizing the predictive performance of a model across a non-stationary stream of data. Unfortunately, CL models tend to forget previous knowledge, thus often underperforming when compared with an offline model tra
Externí odkaz:
http://arxiv.org/abs/2404.07817
Autor:
Nascimento, Julio A. do, Hasnip, Phil J., Cavill, S. A., Cossu, Fabrizio, Kepaptsoglou, Demie, Ramasse, Quentin M., Kerrigan, Adam, Lazarov, Vlado K.
We explore the inelastic spectra of electrons impinging in a magnetic system. The methodology here presented is intended to highlight the charge-dependent interaction of the electron beam in a STEM-EELS experiment, and the local vector potential gene
Externí odkaz:
http://arxiv.org/abs/2401.12302
Autor:
Verwimp, Eli, Aljundi, Rahaf, Ben-David, Shai, Bethge, Matthias, Cossu, Andrea, Gepperth, Alexander, Hayes, Tyler L., Hüllermeier, Eyke, Kanan, Christopher, Kudithipudi, Dhireesha, Lampert, Christoph H., Mundt, Martin, Pascanu, Razvan, Popescu, Adrian, Tolias, Andreas S., van de Weijer, Joost, Liu, Bing, Lomonaco, Vincenzo, Tuytelaars, Tinne, van de Ven, Gido M.
Publikováno v:
Transactions on Machine Learning Research (TMLR), 2024
Continual learning is a subfield of machine learning, which aims to allow machine learning models to continuously learn on new data, by accumulating knowledge without forgetting what was learned in the past. In this work, we take a step back, and ask
Externí odkaz:
http://arxiv.org/abs/2311.11908
Publikováno v:
npj Quantum Materials, Vol 9, Iss 1, Pp 1-8 (2024)
Abstract Co-based honeycomb magnets have been actively studied recently for the potential realization of emergent quantum magnetism therein such as the Kitaev spin liquid. Here we employ density functional and dynamical mean-field theory methods to e
Externí odkaz:
https://doaj.org/article/2abd886699ab4710a534512f805a3c44
Autor:
Annabella Di Mauro, Mariachiara Santorsola, Giovanni Savarese, Roberto Sirica, Monica Ianniello, Alessia Maria Cossu, Anna Ceccarelli, Francesco Sabbatino, Marco Bocchetti, Anna Chiara Carratù, Francesca Pentimalli, Gerardo Ferrara, Guglielmo Nasti, Michele Caraglia, Alessandro Ottaiano
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-11 (2024)
Abstract Background Microsatellite instability (MSI) is a well-established predictive biomarker for immune checkpoint inhibitor (ICI) response in metastatic colon cancer. Both high MSI and tumor mutational burden (TMB) are markers of genomic instabil
Externí odkaz:
https://doaj.org/article/2511af399ba9499ab479b1e841ab980d
Autor:
Piera Grisolia, Rossella Tufano, Clara Iannarone, Antonio De Falco, Francesca Carlino, Cinzia Graziano, Raffaele Addeo, Marianna Scrima, Francesco Caraglia, Anna Ceccarelli, Pier Vitale Nuzzo, Alessia Maria Cossu, Stefano Forte, Raffaella Giuffrida, Michele Orditura, Michele Caraglia, Michele Ceccarelli
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-12 (2024)
Abstract Background Recent studies have highlighted the importance of the cell-free DNA (cfDNA) methylation profile in detecting breast cancer (BC) and its different subtypes. We investigated whether plasma cfDNA methylation, using cell-free Methylat
Externí odkaz:
https://doaj.org/article/b4709ad2f11d40968a2b2c09a3828f5f
Autor:
Soutif--Cormerais, Albin, Carta, Antonio, Cossu, Andrea, Hurtado, Julio, Hemati, Hamed, Lomonaco, Vincenzo, Van de Weijer, Joost
Online continual learning aims to get closer to a live learning experience by learning directly on a stream of data with temporally shifting distribution and by storing a minimum amount of data from that stream. In this empirical evaluation, we evalu
Externí odkaz:
http://arxiv.org/abs/2308.10328
Autor:
A.M. Rich, W. Rubin, S. Rickli, T. Akhmetshina, J. Cossu, L. Berger, M. Magno, K.M. Nuss, B. Schaller, J.F. Löffler
Publikováno v:
Bioactive Materials, Vol 43, Iss , Pp 603-618 (2025)
Biodegradable magnesium is a highly desired material for fracture fixation implants because of its good mechanical properties and ability to completely dissolve in the body over time, eliminating the need for a secondary surgery to remove the implant
Externí odkaz:
https://doaj.org/article/8687dbcec5af4fdfb25cf08ca780e508