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Extrinsic local regression on manifold-valued data

Extrinsic local regression on manifold-valued data

10 August 2015
Lizhen Lin
Brian St. Thomas
Hongtu Zhu
David B. Dunson
ArXiv (abs)PDFHTML

Papers citing "Extrinsic local regression on manifold-valued data"

18 / 18 papers shown
DFNN: A Deep Fréchet Neural Network Framework for Learning Metric-Space-Valued Responses
DFNN: A Deep Fréchet Neural Network Framework for Learning Metric-Space-Valued Responses
Kyum Kim
Yaqing Chen
Paromita Dubey
157
2
0
20 Oct 2025
Dynamical local Fréchet curve regression in manifolds
Dynamical local Fréchet curve regression in manifolds
M.D. Ruiz-Medina
A. Torres--Signes
290
0
0
08 May 2025
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures
Sophia Sanborn
Sophia Sanborn
Johan Mathe
Louisa Cornelis
Abby Bertics
...
Hansen Lillemark
Christian Shewmake
Fatih Dinc
Xavier Pennec
Nina Miolane
415
20
0
12 Jul 2024
Semi-supervised Fréchet Regression
Semi-supervised Fréchet Regression
Rui Qiu
Zhou Yu
Zhenhua Lin
207
0
0
16 Apr 2024
Deep Extrinsic Manifold Representation for Vision Tasks
Deep Extrinsic Manifold Representation for Vision Tasks
Tongtong Zhang
Xian Wei
Yuanxiang Li
450
0
0
31 Mar 2024
Intrinsic and extrinsic deep learning on manifolds
Intrinsic and extrinsic deep learning on manifoldsElectronic Journal of Statistics (EJS), 2023
Yi-Zheng Fang
Ilsang Ohn
Vijay Gupta
Lizhen Lin
220
5
0
16 Feb 2023
Hessian Based Smoothing Splines for Manifold Learning
Hessian Based Smoothing Splines for Manifold Learning
Juno Kim
227
0
0
10 Feb 2023
Extrinsic Bayesian Optimizations on Manifolds
Extrinsic Bayesian Optimizations on Manifolds
Yi-Zheng Fang
Mu Niu
P. Cheung
Lizhen Lin
316
1
0
21 Dec 2022
Sliced Inverse Regression in Metric Spaces
Sliced Inverse Regression in Metric SpacesStatistica sinica (SS), 2022
Joni Virta
Kuang‐Yao Lee
Lexin Li
181
10
0
23 Jun 2022
Functional additive models on manifolds of planar shapes and forms
Functional additive models on manifolds of planar shapes and formsJournal of Computational And Graphical Statistics (JCGS), 2021
Almond Stocker
Lisa Steyer
S. Greven
485
8
0
06 Sep 2021
Gaussian Process Subspace Regression for Model Reduction
Gaussian Process Subspace Regression for Model Reduction
Ruda Zhang
Simon Mak
David B. Dunson
GP
290
5
0
09 Jul 2021
Robust Optimization and Inference on Manifolds
Robust Optimization and Inference on ManifoldsStatistica sinica (SS), 2020
Lizhen Lin
Drew Lazar
Bayan Sarpabayeva
David B. Dunson
188
8
0
11 Jun 2020
Stochastic Zeroth-order Riemannian Derivative Estimation and
  Optimization
Stochastic Zeroth-order Riemannian Derivative Estimation and Optimization
Jiaxiang Li
Krishnakumar Balasubramanian
Shiqian Ma
389
5
0
25 Mar 2020
Functional PCA with Covariate Dependent Mean and Covariance Structure
Functional PCA with Covariate Dependent Mean and Covariance Structure
Fei Ding
Shiyuan He
David E. Jones
Jianhua Z. Huang
294
9
0
30 Jan 2020
Optimal Design of Experiments on Riemannian Manifolds
Optimal Design of Experiments on Riemannian ManifoldsJournal of the American Statistical Association (JASA), 2019
Hang Li
Enrique Del Castillo
260
5
0
06 Nov 2019
Gaussian Process Landmarking on Manifolds
Gaussian Process Landmarking on Manifolds
Tingran Gao
S. Kovalsky
Ingrid Daubechies
573
41
0
09 Feb 2018
Connecting pairwise spheres by depth: DCOPS
Connecting pairwise spheres by depth: DCOPS
R. Fraiman
Fabrice Gamboa
L. Moreno
MDE
360
12
0
06 Oct 2017
Principal Component Analysis for Functional Data on Riemannian Manifolds
  and Spheres
Principal Component Analysis for Functional Data on Riemannian Manifolds and Spheres
Xiongtao Dai
Hans-Georg Müller
211
90
0
17 May 2017
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