Results 171 to 180 of about 24,975 (207)

Riemannian geometry for efficient analysis of protein dynamics data. [PDF]

Proc Natl Acad Sci U S A
Diepeveen W, Esteve-Yagüe C, Lellmann J, Öktem O, Schönlieb CB.   +4 more
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Fast convergence of trust-regions for non-isolated minima via analysis of CG on indefinite matrices. [PDF]

Math Program
Rebjock Q, Boumal N.
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Comprehensive review of dimensionality reduction algorithms: challenges, limitations, and innovative solutions. [PDF]

PeerJ Comput Sci
Wani AA.
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Assessing and improving reliability of neighbor embedding methods: a map-continuity perspective. [PDF]

Nat Commun
Liu Z, Ma R, Zhong Y.
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From latent dynamics to data geometry: Nonlinear diffusion modelling for protein structures. [PDF]

Comput Struct Biotechnol J
Liang X, Paquet E, Viktor H, Michalowski W.   +3 more
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Phosphine-catalyzed β-C(sp³)-H functionalization of cyclic amines <i>via</i> a halogen based frustrated radical pairs approach. [PDF]

Chem Sci
Xie Y, Meng X, Liu C, Tan J, Zhang X, Zhang Z, Dong S, Liang T.   +7 more
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SRE-FMaps: A Sinkhorn-Regularized Elastic Functional Map Framework for Non-Isometric 3D Shape Matching. [PDF]

J Imaging
Zhang D, Zhang Y, Wang N, Zhao D.
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Robust estimation of the intrinsic dimension of data sets with quantum cognition machine learning. [PDF]

Sci Rep
Candelori L, Abanov AG, Berger J, Hogan CJ, Kirakosyan V, Musaelian K, Samson R, Smith JET, Villani D, Wells MT, Xu M.   +10 more
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Ricci curvature bounds and rigidity for non-smooth Riemannian and semi-Riemannian metrics. [PDF]

Manuscr Math
Kunzinger M, Ohanyan A, Vardabasso A.
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Self-similar Hessian and conformally Kähler manifolds

Annals of Global Analysis and Geometry, 2022
This paper is devoted to the study of self-similar Hessian and special Kähler manifolds. Recall that a Hessian manifold is an affine manifold with a Riemannian metric which is locally equivalent to the Hessian of a function. Any Kähler metric can be locally defined as a complex Hessian \(\partial \bar{\partial}\varphi\).
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