1 citations · 3 across the 6 of their papers we have counts for
6 papers
Gamow shell model description of the hypernuclei
Alan Cruz Dassie, Emiko Hiyama, Nicolas Michel +1
Hypernuclear physics studies baryon interactions and the structure of exotic atomic nuclei, where strangeness plays a key role in dense matter. High-resolution -ray spectroscopy…
Gamow shell model description of neutron-rich He hyper-isotopes
Xin Li, N. Michel, J. G. Li +1
The Gamow shell model (GSM) framework has been extended to the study of weakly bound hypernuclei. As a first application, the neutron-rich He hyper-isotope chains, from 6ΛHe to 9ΛH…
Domain-Aware Augmentations for Unsupervised Online General Continual Learning
Nicolas Michel, Romain Negrel, Giovanni Chierchia +1
Continual Learning has been challenging, especially when dealing with unsupervised scenarios such as Unsupervised Online General Continual Learning (UOGCL), where the learning agen…
New metrics for analyzing continual learners
Nicolas Michel, Giovanni Chierchia, Romain Negrel +2
Deep neural networks have shown remarkable performance when trained on independent and identically distributed data from a fixed set of classes. However, in real-world scenarios, i…
Learning Representations on the Unit Sphere: Investigating Angular Gaussian and von Mises-Fisher Distributions for Online Continual Learning
Nicolas Michel, Giovanni Chierchia, Romain Negrel +1
We use the maximum a posteriori estimation principle for learning representations distributed on the unit sphere. We propose to use the angular Gaussian distribution, which corresp…
Contrastive Learning for Online Semi-Supervised General Continual Learning
Nicolas Michel, Romain Negrel, Giovanni Chierchia +1
We study Online Continual Learning with missing labels and propose SemiCon, a new contrastive loss designed for partly labeled data. We demonstrate its efficiency by devising a mem…