The Sub-Riemannian Geometry of Contact Manifolds
This paper explores the intricate relationship between sub-Riemannian geometry and contact manifolds, two fundamental areas of modern differential geometry with profound implications in fields ranging from optimal control theory to theoretical physics. Sub-Riemannian geometry, characterized by a metric defined on a non-integrable distribution, provides
Revista, Zen, MATH, 10
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Geometry of sub-Riemannian diffusion processes
Sub-Riemannian geometry is the natural setting for studying dynamical systems, as noise often has a lower dimension than the dynamics it enters. This makes sub-Riemannian geometry an important field of study. In this thesis, we analysis some of the aspects of sub-Riemannian diffusion processes on manifolds.
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A Band-Aware Riemannian Network with Domain Adaptation for Motor Imagery EEG Signal Decoding. [PDF]
Wang Z, Ma Y, Du Y, She Q.
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Filter bank CSP with Riemannian weighting for disability-centric motor imagery brain computer interface. [PDF]
Jihen S +4 more
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Viscosity solutions to the ∞-Laplace equation in Grushin-type spaces
In this paper, we prove the existence and uniqueness of viscosity solutions to the infinite Laplace equation in Grushin-type spaces whose tangent spaces consist of arbitrary triangular vector fields.
Thomas Bieske, Zachary Forrest
doaj
RMETNet: A cross-subject motor imagery EEG signal classification model based on TSLANet and riemannian geometry features. [PDF]
Zhao Y +9 more
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Connected Components on Lie Groups and Applications to Multi-Orientation Image Analysis. [PDF]
van den Berg NJ, Mula O, Vis L, Duits R.
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Thermodynamics à la Souriau on Kähler Non-Compact Symmetric Spaces for Cartan Neural Networks. [PDF]
Fré PG, Sorin AS, Trigiante M.
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Surface measure on, and the local geometry of, sub-Riemannian manifolds. [PDF]
Don S, Magnani V.
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Diffusion-Shock PDEs for Deep Learning on Position-Orientation Space. [PDF]
Sherry FM, Schaefer K, Duits R.
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