Zobrazeno 1 - 10
of 6 961
pro vyhledávání: '"P. Beretta"'
Autor:
Beretta, D.
This article presents an open-source Python package for simulating micro-thermoelectric generators, based on the work by D. Beretta et al. (Sustainable Energy Fuels, 2017). Featuring a user-friendly graphical user interface and robust computational c
Externí odkaz:
http://arxiv.org/abs/2412.05954
In this paper, we focus on estimating the causal effect of an intervention over time on a dynamical system. To that end, we formally define causal interventions and their effects over time on discrete-time stochastic processes (DSPs). Then, we show u
Externí odkaz:
http://arxiv.org/abs/2410.10502
We consider the inverse problem of determining an elastic dislocation that models a seismic fault in the quasi-static regime of aseismic, creeping faults, from displacement measurements made at the surface of Earth. We derive both a distributed as we
Externí odkaz:
http://arxiv.org/abs/2410.04273
In this paper, we tackle the problem of reconstructing earlier tumour configurations starting from a single spatial measurement at a later time. We describe the tumour evolution through a diffuse interface model coupling a Cahn-Hilliard-type equation
Externí odkaz:
http://arxiv.org/abs/2409.15925
Current uncertainty quantification is memory and compute expensive, which hinders practical uptake. To counter, we develop Sketched Lanczos Uncertainty (SLU): an architecture-agnostic uncertainty score that can be applied to pre-trained neural networ
Externí odkaz:
http://arxiv.org/abs/2409.15008
The development of mathematical models of cancer informed by time-resolved measurements has enabled personalised predictions of tumour growth and treatment response. However, frequent cancer monitoring is rare, and many tumours are treated soon after
Externí odkaz:
http://arxiv.org/abs/2409.12844
The increase of renewable energy generation towards the zero-emission target is making the problem of controlling power grids more and more challenging. The recent series of competitions Learning To Run a Power Network (L2RPN) have encouraged the use
Externí odkaz:
http://arxiv.org/abs/2409.04467
Classical shadow (CS) has opened the door to predicting the characteristics of quantum systems using very few measurements. As quantum systems grow in size, new ways to characterize them are needed to show the quality of their qubits, gates, and how
Externí odkaz:
http://arxiv.org/abs/2408.17317
Autor:
Woodland, McKell, Patel, Nihil, Castelo, Austin, Taie, Mais Al, Eltaher, Mohamed, Yung, Joshua P., Netherton, Tucker J., Calderone, Tiffany L., Sanchez, Jessica I., Cleere, Darrel W., Elsaiey, Ahmed, Gupta, Nakul, Victor, David, Beretta, Laura, Patel, Ankit B., Brock, Kristy K.
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2024) 2006
Clinically deployed deep learning-based segmentation models are known to fail on data outside of their training distributions. While clinicians review the segmentations, these models tend to perform well in most instances, which could exacerbate auto
Externí odkaz:
http://arxiv.org/abs/2408.02761
In this paper, we consider the monodomain model of cardiac electrophysiology. After an analysis of the well-posedness of the forward problem, we show that perfectly insulating regions (modeling ischemic regions in the cardiac tissue) can be uniquely
Externí odkaz:
http://arxiv.org/abs/2407.08863