Zobrazeno 1 - 10
of 9 880
pro vyhledávání: '"PEREIRA, A. C."'
Autor:
Costa, Miguel, Petersen, Morten W., Vandervoort, Arthur, Drews, Martin, Morrissey, Karyn, Pereira, Francisco C.
Publikováno v:
Tackling Climate Change with Machine Learning workshop at NeurIPS 2024
Due to climate change the frequency and intensity of extreme rainfall events, which contribute to urban flooding, are expected to increase in many places. These floods can damage transport infrastructure and disrupt mobility, highlighting the need fo
Externí odkaz:
http://arxiv.org/abs/2409.18574
When a dynamical system is subject to a periodic perturbation, the averaging method can be applied to obtain an autonomous leading order `guiding system', placing the time dependence at higher orders. Recent research focused on investigating invarian
Externí odkaz:
http://arxiv.org/abs/2409.11054
Autor:
Pereira, João C., Klenze, Tobias, Giampietro, Sofia, Limbeck, Markus, Spiliopoulos, Dionysios, Wolf, Felix A., Eilers, Marco, Sprenger, Christoph, Basin, David, Müller, Peter, Perrig, Adrian
We present the first formally-verified Internet router, which is part of the SCION Internet architecture. SCION routers run a cryptographic protocol for secure packet forwarding in an adversarial environment. We verify both the protocol's network-wid
Externí odkaz:
http://arxiv.org/abs/2405.06074
Publikováno v:
Bulletin des Sciences Mathematiques, Volume 190, 2024, 103378
Floquet's Theorem is a celebrated result in the theory of ordinary differential equations. Essentially, the theorem states that, when studying a linear differential system with $T$-periodic coefficients, we can apply a, possibly complex, $T$-periodic
Externí odkaz:
http://arxiv.org/abs/2312.05608
Refinement transforms an abstract system model into a concrete, executable program, such that properties established for the abstract model carry over to the concrete implementation. Refinement has been used successfully in the development of substan
Externí odkaz:
http://arxiv.org/abs/2311.14452
The ability to learn polynomials and generalize out-of-distribution is essential for simulation metamodels in many disciplines of engineering, where the time step updates are described by polynomials. While feed forward neural networks can fit any fu
Externí odkaz:
http://arxiv.org/abs/2307.10892
Publikováno v:
Mathematische Annalen (2024) 389:543-590
Important information about the dynamical structure of a differential system can be revealed by looking into its invariant compact manifolds, such as equilibria, periodic orbits, and invariant tori. This knowledge is significantly increased if asympt
Externí odkaz:
http://arxiv.org/abs/2305.11821
Autor:
Gammelli, Daniele, Harrison, James, Yang, Kaidi, Pavone, Marco, Rodrigues, Filipe, Pereira, Francisco C.
Optimization problems over dynamic networks have been extensively studied and widely used in the past decades to formulate numerous real-world problems. However, (1) traditional optimization-based approaches do not scale to large networks, and (2) th
Externí odkaz:
http://arxiv.org/abs/2305.09129
Autor:
Pereira, Ingrid C. S.1 (AUTHOR) ingrid_13@metalmat.ufrj.br, de Sousa, José Renato M.2 (AUTHOR) jrenato@laceo.coppe.ufrj.br, Costa, Celio A.1 (AUTHOR) celio@metalmat.ufrj.br
Publikováno v:
Polymers (20734360). Oct2024, Vol. 16 Issue 20, p2906. 18p.
Hilbert's 16th Problem, about the maximum number of limit cycles of planar polynomial vector fields of a given degree $m$, has been one of the most important driving forces for new developments in the qualitative theory of vector fields. Increasing t
Externí odkaz:
http://arxiv.org/abs/2212.12006