Zobrazeno 1 - 10
of 2 783
pro vyhledávání: '"Urbani, P."'
In many large-scale classification problems, classes are organized in a known hierarchy, typically represented as a tree expressing the inclusion of classes in superclasses. We introduce a loss for this type of supervised hierarchical classification.
Externí odkaz:
http://arxiv.org/abs/2411.16438
In this work we analyse the small-time reachability properties of a nonlinear parabolic equation, by means of a bilinear control, posed on a torus of arbitrary dimension $d$. Under a saturation hypothesis on the control operators, we show the small-t
Externí odkaz:
http://arxiv.org/abs/2407.10521
Generative modeling aims at producing new datapoints whose statistical properties resemble the ones in a training dataset. In recent years, there has been a burst of machine learning techniques and settings that can achieve this goal with remarkable
Externí odkaz:
http://arxiv.org/abs/2405.10822
Autor:
Urbani, Pierfrancesco
The purpose of this manuscript is to review my recent activity on three main research topics. The first concerns the nature of low temperature amorphous solids and their relation with the spin glass transition in a magnetic field. This is the subject
Externí odkaz:
http://arxiv.org/abs/2405.06384
Autor:
P. Montone, S. Pierdominici, M. T. Mariucci, F. Mirabella, M. Urbani, A. Akimbekova, L. Chiaraluce, W. Johnson, M. R. Barchi
Publikováno v:
Solid Earth, Vol 15, Pp 1385-1406 (2024)
The International Continental Scientific Drilling Program (ICDP) STAR (A Strainmeter Array Along the Alto Tiberina Fault System) drilling project aims to study the seismic and aseismic fault slip behavior of the active low-angle Alto Tiberina normal
Externí odkaz:
https://doaj.org/article/a285f39255fc45ddb7f658e475a585ca
Stochastic Gradient Descent (SGD) is an out-of-equilibrium algorithm used extensively to train artificial neural networks. However very little is known on to what extent SGD is crucial for to the success of this technology and, in particular, how muc
Externí odkaz:
http://arxiv.org/abs/2309.04788
By exploiting the modular RISC-V ISA this paper presents the customization of instruction set with posit\textsuperscript{\texttrademark} arithmetic instructions to provide improved numerical accuracy, well-defined behavior and increased range of repr
Externí odkaz:
http://arxiv.org/abs/2308.03425
Publikováno v:
SciPost Phys. 15, 219 (2023)
We consider a recently proposed model to understand the rigidity transition in confluent tissues and we derive the dynamical mean field theory (DMFT) equations that describes several types of dynamics of the model in the thermodynamic limit: gradient
Externí odkaz:
http://arxiv.org/abs/2306.06420
In many complex systems, elementary units live in a chaotic environment and need to adapt their strategies to perform a task, by extracting information from the environment and controlling the feedback loop on it. One of the main example of systems o
Externí odkaz:
http://arxiv.org/abs/2306.01477
The role of uncertainty in data management has become more prominent than ever before, especially because of the growing importance of machine learning-driven applications that produce large uncertain databases. A well-known approach to querying such
Externí odkaz:
http://arxiv.org/abs/2304.05459