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Geodesic Exponential Kernels: When Curvature and Linearity Conflict

2 November 2014

Papers citing "Geodesic Exponential Kernels: When Curvature and Linearity Conflict"

22 / 72 papers shown

Title
Wasserstein Weisfeiler-Lehman Graph Kernels Matteo Togninalli M. Ghisu Felipe Llinares-López Bastian Rieck Karsten Borgwardt 76 201 0 04 Jun 2019
Probabilistic Kernel Support Vector Machines Yongxin Chen T. Georgiou Allen Tannenbaum 27 1 0 14 Apr 2019
Fast and Robust Shortest Paths on Manifolds Learned from Data Georgios Arvanitidis Søren Hauberg Philipp Hennig Michael Schober 69 37 0 22 Jan 2019
Poincaré Wasserstein Autoencoder Ivan Ovinnikov 77 17 0 05 Jan 2019
Generalization Properties of hyper-RKHS and its Applications Fanghui Liu Lei Shi Xiaolin Huang Jie Yang Johan A. K. Suykens 46 4 0 26 Sep 2018
Semi-convolutional Operators for Instance Segmentation David Novotny Samuel Albanie Diane Larlus Andrea Vedaldi ISeg 70 85 0 27 Jul 2018
Convex Class Model on Symmetric Positive Definite Manifolds Kun-li Zhao Arnold Wiliem Shaokang Chen Brian C. Lovell 42 8 0 14 Jun 2018
Dictionary Learning and Sparse Coding on Statistical Manifolds Rudrasis Chakraborty Monami Banerjee B. Vemuri 31 0 0 03 May 2018
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams Tam Le M. Yamada 107 80 0 10 Feb 2018
Supervised Learning with Indefinite Topological Kernels T. Padellini P. Brutti 52 6 0 20 Sep 2017
cvpaper.challenge in 2016: Futuristic Computer Vision through 1,600 Papers Survey Hirokatsu Kataoka Soma Shirakabe Yun He S. Ueta Teppei Suzuki ... Ryousuke Takasawa Masataka Fuchida Yudai Miyashita Kazushige Okayasu Yuta Matsuzaki 83 1 0 20 Jul 2017
Sliced Wasserstein Kernel for Persistence Diagrams Mathieu Carrière Marco Cuturi S. Oudot 76 239 0 11 Jun 2017
Multivariate Regression with Gross Errors on Manifold-valued Data Xiaowei Zhang Xudong Shi Yu Sun Li Cheng 38 8 0 26 Mar 2017
A Gaussian Process Regression Model for Distribution Inputs François Bachoc Fabrice Gamboa Jean-Michel Loubes N. Venet 86 53 0 31 Jan 2017
Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification H. Q. Minh Marco San-Biagio Loris Bazzani Vittorio Murino 34 3 0 29 Sep 2016
cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey Hirokatsu Kataoka Yudai Miyashita Tomoaki K. Yamabe Soma Shirakabe Shin-ichi Sato ... Kaori Abe Takaaki Imanari Naomichi Kobayashi Shinichiro Morita Akio Nakamura 47 2 0 26 May 2016
Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods Mehrtash Harandi Mathieu Salzmann Leonid Sigal 60 193 0 20 May 2016
An information theoretic formulation of the Dictionary Learning and Sparse Coding Problems on Statistical Manifolds Rudrasis Chakraborty Monami Banerjee Victoria G. Crawford B. Vemuri 32 1 0 23 Apr 2016
Sliced Wasserstein Kernels for Probability Distributions Soheil Kolouri Yang Zou Gustavo K. Rohde 85 161 0 10 Nov 2015
Efficient Clustering on Riemannian Manifolds: A Kernelised Random Projection Approach Kun-li Zhao A. Alavi Arnold Wiliem Brian C. Lovell 39 23 0 18 Sep 2015
Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs Mehrtash Harandi Mathieu Salzmann Mahsa Baktash 52 48 0 31 Jul 2015
Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices A. Cherian S. Sra 62 119 0 10 Jul 2015