287 citations
- IkerbasqueES170 papers
- University of the Basque CountryES145 papers
- Centre National de la Recherche ScientifiqueFR27 papers
- Romanian AcademyRO16 papers
- Universidad Autónoma de MadridES14 papers
- Universidade de São PauloBR13 papers
- Universidad Carlos III de MadridES12 papers
- University of PotsdamDE12 papers
- IMAR - Institutul de Matematică „Simion Stoilow” al Academiei RomâneRO9 papers
- Association of Electronic and Information TechnologiesES8 papers
- École Polytechnique Fédérale de LausanneCH8 papers
- Institute of Mathematical SciencesIN8 papers
448 papers
First-return time in fractional kinetics
M. Dahlenburg G. Pagnini
The first-return time is the time that it takes a random walker to go back to the initial position for the first time. We study the first-return time when random walkers perform fr…
Disentangling Aleatoric and Epistemic Uncertainty in Physics-Informed Neural Networks. Application to Insulation Material Degradation Prognostics
Ibai Ramirez, Jokin Alcibar, Joel Pino +2
Physics-Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains…
Degenerate Poincaré-Sobolev inequalities via fractional integration
Alejandro Claros
We present a local weighted estimate for the Riesz potential in , which improves the main theorem of Alberico, Cianchi, and Sbordone [C. R. Math. Acad. Sci. Paris \te…
Tight bound for the total time in digital-analog quantum computation
Mikel Garcia-de-Andoin, Mikel Sanz
Digital-analog quantum computing (DAQC) is a universal computational paradigm that combines the evolution under an entangling Hamiltonian with the application of single-qubit gates…
-like phase transitions from square roots of supersymmetric Hamiltonians
Jacob L. Barnett, Ramy El-Ganainy
We introduce a general framework for realizing -like phase transitions in non-Hermitian systems without imposing explicit parity--time () symmetry. The…
Complexity of Activity Patterns in a Bio-Inspired Hopfield-Type Network in Different Topologies
Marco Cafiso, Paolo Paradisi
Neural network models capable of storing memory have been extensively studied in computer science and computational neuroscience. The Hopfield network is a prototypical example of…