Zobrazeno 1 - 10
of 2 147
pro vyhledávání: '"Geelen, P"'
This paper presents a probabilistic approach to represent and quantify model-form uncertainties in the reduced-order modeling of complex systems using operator inference techniques. Such uncertainties can arise in the selection of an appropriate stat
Externí odkaz:
http://arxiv.org/abs/2409.00220
Melchior's inequality implies that the average line-length in a simple, rank-$3$, real-representable matroid is less than $3$. A similar result holds for complex-representable matroids, using Hirzebruch's inequality, but with a weaker bound of $4$. W
Externí odkaz:
http://arxiv.org/abs/2310.02826
Autor:
Damci A, Hoeijmakers JG, den Hollander M, Faber CG, Waardenburg S, van Laake-Geelen CCM, Köke AJ, Verbunt JA
Publikováno v:
Journal of Pain Research, Vol Volume 17, Pp 3997-4010 (2024)
Aysun Damci,1,2 Janneke GJ Hoeijmakers,1,2 Marlies den Hollander,3– 5 Catharina G Faber,1,2 Sophie Waardenburg,6,7 Charlotte CM van Laake-Geelen,3– 5 Albère JA Köke,3,4 Jeanine AMCF Verbunt3– 5 1MHeNS, Mental Health and Neuroscience Research
Externí odkaz:
https://doaj.org/article/1eca81a053b642ab9794141f6e881e3d
Autor:
Julia Dixon-Douglas, Balaji Virassamy, Kylie Clarke, Michael Hun, Stephen J. Luen, Peter Savas, Courtney T. van Geelen, Steven David, Prudence A. Francis, Roberto Salgado, Stefan Michiels, Sherene Loi
Publikováno v:
npj Breast Cancer, Vol 10, Iss 1, Pp 1-10 (2024)
Abstract The role of adaptive immunity in long-term outcomes in early breast cancer is increasingly recognised. Standard (neo)adjuvant chemotherapy can have adverse effects on immune cells. We conducted a retrospective longitudinal study of full bloo
Externí odkaz:
https://doaj.org/article/ebb3661436284d6cab4b8c2b69e1d8ff
Autor:
Geelen, Jim, Kroeker, Matthew E.
We show that, for any prime $p$ and integer $k \geq 2$, a simple GF($p$)-representable matroid with sufficiently high rank has a rank-$k$ flat which is either independent in $M$, or is a projective or affine geometry. As a corollary we obtain a Ramse
Externí odkaz:
http://arxiv.org/abs/2309.15185
We present a novel method for learning reduced-order models of dynamical systems using nonlinear manifolds. First, we learn the manifold by identifying nonlinear structure in the data through a general representation learning problem. The proposed ap
Externí odkaz:
http://arxiv.org/abs/2308.02802
We present a novel framework for learning cost-efficient latent representations in problems with high-dimensional state spaces through nonlinear dimension reduction. By enriching linear state approximations with low-order polynomial terms we account
Externí odkaz:
http://arxiv.org/abs/2306.13748
This work presents two novel approaches for the symplectic model reduction of high-dimensional Hamiltonian systems using data-driven quadratic manifolds. Classical symplectic model reduction approaches employ linear symplectic subspaces for represent
Externí odkaz:
http://arxiv.org/abs/2305.15490
Autor:
W. Daniel Kissling, Julian C. Evans, Rotem Zilber, Tom D. Breeze, Stacy Shinneman, Lindy C. Schneider, Carl Chalmers, Paul Fergus, Serge Wich, Luc H.W.T. Geelen
Publikováno v:
Basic and Applied Ecology, Vol 79, Iss , Pp 141-152 (2024)
Modern approaches with advanced technology can automate and expand the extent and resolution of biodiversity monitoring. We present the development of an innovative system for automated wildlife monitoring in a coastal Natura 2000 nature reserve of t
Externí odkaz:
https://doaj.org/article/73e379a790fc48e2a76ebb9f7bce90fa
Autor:
Geelen, Jim, Kroeker, Matthew E.
The Sylvester-Gallai Theorem states that every rank-$3$ real-representable matroid has a two-point line. We prove that, for each $k\ge 2$, every complex-representable matroid with rank at least $4^{k-1}$ has a rank-$k$ flat with exactly $k$ points. F
Externí odkaz:
http://arxiv.org/abs/2212.03307