Zobrazeno 1 - 10
of 3 906
pro vyhledávání: '"Uriarte P"'
Autor:
Renz, Jessica, Dauda, Kazeem A., Aga, Olav N. L., Diaz-Uriarte, Ramon, Löhr, Iren H., Blomberg, Bjørn, Johnston, Iain G.
Can we understand and predict the evolutionary pathways by which bacteria acquire multi-drug resistance (MDR)? These questions have substantial potential impact in basic biology and in applied approaches to address the global health challenge of anti
Externí odkaz:
http://arxiv.org/abs/2411.00219
Developing efficient methods for solving parametric partial differential equations is crucial for addressing inverse problems. This work introduces a Least-Squares-based Neural Network (LS-Net) method for solving linear parametric PDEs. It utilizes a
Externí odkaz:
http://arxiv.org/abs/2410.15089
The evolution of a vortex line following the binormal flow equation (i.e. with a velocity proportional to the local curvature in the direction of the binormal vector) has been postulated as an approximation for the evolution of vortex filaments in bo
Externí odkaz:
http://arxiv.org/abs/2410.05971
Variational Physics-Informed Neural Networks often suffer from poor convergence when using stochastic gradient-descent-based optimizers. By introducing a Least Squares solver for the weights of the last layer of the neural network, we improve the con
Externí odkaz:
http://arxiv.org/abs/2407.20417
Density-based distances (DBDs) offer an elegant solution to the problem of metric learning. By defining a Riemannian metric which increases with decreasing probability density, shortest paths naturally follow the data manifold and points are clustere
Externí odkaz:
http://arxiv.org/abs/2407.09297
Autor:
Galindo-Uriarte, Oscar, Breton, Nora
We present the two exact solutions of the Einstein-Nonlinear electrodynamics equations that generalize the Kerr-Newman solution. We determined the generalized electromagnetic potentials using the alignment between the tetrad vectors of the metric and
Externí odkaz:
http://arxiv.org/abs/2406.17077
We develop and implement numerically a phase field model for the evolution and detachment of a gas bubble resting on a solid substrate and surrounded by a viscous liquid. The bubble has a static contact angle $\theta $ and will be subject to gravitat
Externí odkaz:
http://arxiv.org/abs/2403.12246
Autor:
Uriarte, Carlos
Partial differential equations have a wide range of applications in modeling multiple physical, biological, or social phenomena. Therefore, we need to approximate the solutions of these equations in computationally feasible terms. Nowadays, among the
Externí odkaz:
http://arxiv.org/abs/2403.09001
Publikováno v:
Meccanica (2022) 57:371-399
The stability of integrators dealing with high order Differential Algebraic Equations (DAEs) is a major issue. The usual procedures give rise to instabilities that are not predicted by the usual linear analysis, rendering the common checks (developed
Externí odkaz:
http://arxiv.org/abs/2402.05768
Autor:
Łoś, Marcin, Służalec, Tomasz, Maczuga, Paweł, Vilkha, Askold, Uriarte, Carlos, Paszyński, Maciej
Physics-Informed Neural Networks (PINNs) have been successfully applied to solve Partial Differential Equations (PDEs). Their loss function is founded on a strong residual minimization scheme. Variational Physics-Informed Neural Networks (VPINNs) are
Externí odkaz:
http://arxiv.org/abs/2401.02300