Zobrazeno 1 - 10
of 44 792
pro vyhledávání: '"de Sousa, P"'
Contrastive pretraining can substantially increase model generalisation and downstream performance. However, the quality of the learned representations is highly dependent on the data augmentation strategy applied to generate positive pairs. Positive
Externí odkaz:
http://arxiv.org/abs/2409.10365
We demonstrate that two-dimensional Kramers-Weyl fermions can be engineered in spin-orbit coupled twisted bilayers, where the chiral structure of these moir\'e systems breaks all mirror symmetries, confining Kramers-Weyl fermions to high-symmetry poi
Externí odkaz:
http://arxiv.org/abs/2409.06806
The issue of consistency is crucial in quantum gravity. It has recently been intensively addressed for effective symmetry-reduced models. In this article, we exhaustively study the anomaly freedom of effective loop quantum cosmology with generalized
Externí odkaz:
http://arxiv.org/abs/2409.06441
Autor:
Peng, Wei, Xia, Tian, Ribeiro, Fabio De Sousa, Bosschieter, Tomas, Adeli, Ehsan, Zhao, Qingyu, Glocker, Ben, Pohl, Kilian M.
The number of samples in structural brain MRI studies is often too small to properly train deep learning models. Generative models show promise in addressing this issue by effectively learning the data distribution and generating high-fidelity MRI. H
Externí odkaz:
http://arxiv.org/abs/2409.05585
Autor:
Trias, Carl De Sousa, Mitrea, Mihai, Fiandrotti, Attilio, Cagnazzo, Marco, Chaudhuri, Sumanta, Tartaglione, Enzo
Nowadays, deep neural networks are used for solving complex tasks in several critical applications and protecting both their integrity and intellectual property rights (IPR) has become of utmost importance. To this end, we advance WaterMAS, a substit
Externí odkaz:
http://arxiv.org/abs/2409.03902
Autor:
Cardoso, Lucas Felipe Ferraro, Filho, José de Sousa Ribeiro, Santos, Vitor Cirilo Araujo, Frances, Regiane Silva Kawasaki, Alves, Ronnie Cley de Oliveira
Although fundamental to the advancement of Machine Learning, the classic evaluation metrics extracted from the confusion matrix, such as precision and F1, are limited. Such metrics only offer a quantitative view of the models' performance, without co
Externí odkaz:
http://arxiv.org/abs/2409.03151
Autor:
Adisa, Olumide, Blay, Enio Alterman, Asgari, Yasaman, Di Bona, Gabriele, Dies, Samantha, Jaramillo, Ana Maria, Resende, Paulo H., Leitao, Ana Maria de Sousa
Complexity science, despite its broad scope and potential impact, has not kept pace with fields like artificial intelligence, biotechnology and social sciences in addressing ethical concerns. The field lacks a comprehensive ethical framework, leaving
Externí odkaz:
http://arxiv.org/abs/2409.02002
Autor:
de Sousa, Janislley Oliveira, de Farias, Bruno Carvalho, Filho, Eddie Batista de Lima, Cordeiro, Lucas Carvalho
This study investigates vulnerabilities in dependencies of sampled open-source software (OSS) projects, the relationship between these and overall project security, and how developers' behaviors and practices influence their mitigation. Through analy
Externí odkaz:
http://arxiv.org/abs/2408.14273
Scientific Machine Learning is transforming traditional engineering industries by enhancing the efficiency of existing technologies and accelerating innovation, particularly in modeling chemical reactions. Despite recent advancements, the issue of so
Externí odkaz:
http://arxiv.org/abs/2408.10720
Geometric frustration is known to completely damage kinetic processes of some of the orbitals (and their associated quantum coherence) as to produce flat bands in the non-interacting systems. The impact of introducing additional interaction to the sy
Externí odkaz:
http://arxiv.org/abs/2408.03939