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In this paper, we aim at developing new methods to join machine learning techniques and macroscopic
differential models for vehicular traffic estimation and forecast. It is well known that data-driven and model-
driven approaches have (sometimes complementary) advantages and drawbacks. We consider… |
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The melting of glaciers coming with climate change threatens the heritage of the last glaciation of Europe likely contained in subglacial lakes in Greenland and Svalbard. This aspect urges specialists to focus their studies (theoretical, numerical and on-field) on such fascinating objects. Along… |
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Linear solvers for large and sparse systems are a key element of scientific applications, and their efficient implementation is necessary to harness the computational power of current computers. Algebraic Multigrid (AMG) Preconditioners are a popular ingredient of such linear solvers; this is the… |
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In this paper we propose a new approach to detect clusters in undirected graphs with attributed vertices. The aim is to group vertices which are similar
not only in terms of structural connectivity but also in terms of attribute values.
We incorporate structural and attribute similarities between… |
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The diffusive behaviour of simple random-walk proposals of many Markov Chain
Monte Carlo (MCMC) algorithms results in slow exploration of the state space making inefficient
the convergence to a target distribution. Hamiltonian/Hybrid Monte Carlo (HMC), by introducing fictious momentum variables,… |
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In this paper, we describe some work aimed at upgrading the Alya code with up-to-date parallel linear solvers capable of achieving reliability, efficiency, and scalability in the computation of the pressure field at each time step of the numerical procedure for solving an LES formulation of the… |
