Zobrazeno 1 - 10
of 3 363
pro vyhledávání: '"Bartolucci, P."'
Autor:
Arbor, Nicolas, Bartolucci, Laurent, Dai, Botao, Azhar, Halima El, Galmiche, Pierre, Jarnet, Delphine, de Papigny, Michel de Mathelin, Meyer, Philippe, Seo, Hyewon
Publikováno v:
The 20th international conference on the use of computers in radiation therapy (ICCR), Jul 2024, Lyon, France. pp.834-836
Skin dose in radiotherapy is a key issue for reducing patient side effects, but dose calculations in this high-gradient region remains a challenge. To support radiation therapists and medical physicist in their decisions, a computational tool has bee
Externí odkaz:
http://arxiv.org/abs/2410.21823
Autor:
Bartolucci, Francesca, Carioni, Marcello, Iglesias, José A., Korolev, Yury, Naldi, Emanuele, Vigogna, Stefano
We revisit the mean field parametrization of shallow neural networks, using signed measures on unbounded parameter spaces and duality pairings that take into account the regularity and growth of activation functions. This setting directly leads to th
Externí odkaz:
http://arxiv.org/abs/2410.14591
Non-equilibrium selection pressures were proposed for the formation of oligonucleotides with rich functionalities encoded in their sequences, such as catalysis. Since phase separation was shown to direct various chemical processes, we ask whether con
Externí odkaz:
http://arxiv.org/abs/2410.08778
Image manipulation detection and localization have received considerable attention from the research community given the blooming of Generative Models (GMs). Detection methods that follow a passive approach may overfit to specific GMs, limiting their
Externí odkaz:
http://arxiv.org/abs/2409.17941
We establish the non-degeneracy of bubbling solutions for singular mean field equations when the blow-up points are either regular or non-quantized singular sources. This extends the results from Bartolucci-Jevnikar-Lee-Yang \cite{bart-5}, which focu
Externí odkaz:
http://arxiv.org/abs/2409.04664
Autor:
Bauermann, Jonathan, Bartolucci, Giacomo, Boekhoven, Job, Jülicher, Frank, Weber, Christoph A.
Emulsions ripen with an average droplet size increasing in time. In chemically active emulsions, coarsening can be absent, leading to a non-equilibrium steady state with mono-disperse droplet sizes. By considering a minimal model for phase separation
Externí odkaz:
http://arxiv.org/abs/2409.03629
Debt recycling is an aggressive equity extraction strategy that potentially permits faster repayment of a mortgage. While equity progressively builds up as the mortgage is repaid monthly, mortgage holders may obtain another loan they could use to inv
Externí odkaz:
http://arxiv.org/abs/2405.19104
We introduce a novel large-scale deep learning model for Limit Order Book mid-price changes forecasting, and we name it `HLOB'. This architecture (i) exploits the information encoded by an Information Filtering Network, namely the Triangulated Maxima
Externí odkaz:
http://arxiv.org/abs/2405.18938
We are concerned with Grad-Shafranov type equations, describing in dimension $N=2$ the equilibrium configurations of a plasma in a Tokamak. We obtain a sharp superlinear generalization of the result of Temam (1977) about the linear case, implying the
Externí odkaz:
http://arxiv.org/abs/2405.03203
We exploit cutting-edge deep learning methodologies to explore the predictability of high-frequency Limit Order Book mid-price changes for a heterogeneous set of stocks traded on the NASDAQ exchange. In so doing, we release `LOBFrame', an open-source
Externí odkaz:
http://arxiv.org/abs/2403.09267