v1v2 (latest)

Riemannian batch normalization for SPD neural networks

3 September 2019

Papers citing "Riemannian batch normalization for SPD neural networks"

45 / 45 papers shown

Title
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges Ce Ju Reinmar J. Kobler Antoine Collas M. Kawanabe Cuntai Guan Bertrand Thirion 102 0 0 26 Apr 2025
Learning to Normalize on the SPD Manifold under Bures-Wasserstein Geometry Rui Wang Shaocheng Jin Ziheng Chen Xiaoqing Luo Xiao Wu 79 0 0 01 Apr 2025
Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices Thibault de Surrel Fabien Lotte Sylvain Chevallier Florian Yger 156 1 0 03 Feb 2025
SPDFusion: An Infrared and Visible Image Fusion Network Based on a Non-Euclidean Representation of Riemannian Manifolds Huan Kang Hui Li Tianyang Xu Rui Wang Xiao Wu J. Kittler 147 1 0 16 Nov 2024
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy Ya-Wei Eileen Lin Ronald R. Coifman Zhengchao Wan Ronen Talmon 195 3 0 28 Oct 2024
Representation Learning for Regime detection in Block Hierarchical Financial Markets Alexa Orton Tim Gebbie AIFin 16 0 0 14 Oct 2024
RMLR: Extending Multinomial Logistic Regression into General Geometries Ziheng Chen Yue Song Rui Wang Xiaojun Wu N. Sebe 69 2 0 28 Sep 2024
Classification of Buried Objects from Ground Penetrating Radar Images by using Second Order Deep Learning Models Douba Jafuno A. Mian G. Ginolhac Nickolas Stelzenmuller 56 0 0 20 Sep 2024
Product Geometries on Cholesky Manifolds with Applications to SPD Manifolds Ziheng Chen Yue Song Xiao-Jun Wu N. Sebe 79 2 0 02 Jul 2024
Matrix Manifold Neural Networks++ Xuan Son Nguyen Shuo Yang A. Histace 76 6 0 29 May 2024
Random matrix theory improved Fréchet mean of symmetric positive definite matrices Florent Bouchard A. Mian Malik Tiomoko G. Ginolhac Frédéric Pascal 130 1 0 10 May 2024
A Lie Group Approach to Riemannian Batch Normalization Ziheng Chen Yue Song Yunmei Liu N. Sebe BDL 112 6 0 17 Mar 2024
$V_kD:$ Improving Knowledge Distillation using Orthogonal Projections Roy Miles Ismail Elezi Jiankang Deng 112 10 0 10 Mar 2024
SPD-DDPM: Denoising Diffusion Probabilistic Models in the Symmetric Positive Definite Space Yunchen Li Zhou Yu Gaoqi He Yunhang Shen Ke Li Xing Sun Shaohui Lin DiffM 49 11 0 13 Dec 2023
Riemannian Self-Attention Mechanism for SPD Networks Rui Wang Xiao-Jun Wu Hui Li Josef Kittler 50 1 0 28 Nov 2023
Riemannian Residual Neural Networks Isay Katsman Eric Chen Sidhanth Holalkere Anna Asch Aaron Lou Ser-Nam Lim Christopher De Sa 71 13 0 16 Oct 2023
Deep Geometric Learning with Monotonicity Constraints for Alzheimer's Disease Progression Seungwoo Jeong Wonsik Jung Junghyo Sohn Heung-Il Suk 87 3 0 05 Oct 2023
Modeling Graphs Beyond Hyperbolic: Graph Neural Networks in Symmetric Positive Definite Matrices Weichen Zhao Federico López J. M. Riestenberg Michael Strube Diaaeldin Taha Steve J. Trettel 82 7 0 24 Jun 2023
R-Mixup: Riemannian Mixup for Biological Networks Xuan Kan Zimu Li Hejie Cui Yue Yu Ran Xu Shaojun Yu Zilong Zhang Ying Guo Carl Yang 99 8 0 05 Jun 2023
Riemannian Multinomial Logistics Regression for SPD Neural Networks Ziheng Chen Yue Song Gaowen Liu Ramana Rao Kompella Xiaojun Wu N. Sebe 80 5 0 18 May 2023
Building Neural Networks on Matrix Manifolds: A Gyrovector Space Approach X. Nguyen Shuo Yang 60 11 0 08 May 2023
Differential geometry with extreme eigenvalues in the positive semidefinite cone Cyrus Mostajeran Nathael Da Costa Graham W. Van Goffrier R. Sepulchre 70 4 0 14 Apr 2023
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals Clément Bonet Benoit Malézieux A. Rakotomamonjy Lucas Drumetz Thomas Moreau M. Kowalski Nicolas Courty 96 16 0 10 Mar 2023
Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective from the Time-Frequency Analysis Ce Ju Cuntai Guan 107 22 0 25 Oct 2022
MAtt: A Manifold Attention Network for EEG Decoding Yue Pan Jing-Lun Chou Chunshan Wei 63 43 0 05 Oct 2022
DreamNet: A Deep Riemannian Network based on SPD Manifold Learning for Visual Classification Rui Wang Xiaojun Wu Ziheng Chen Tianyang Xu J. Kittler 37 2 0 16 Jun 2022
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG Reinmar J. Kobler J. Hirayama Qibin Zhao M. Kawanabe 83 58 0 02 Jun 2022
Near out-of-distribution detection for low-resolution radar micro-Doppler signatures Martin Bauw Santiago Velasco-Forero Jesús Angulo C. Adnet O. Airiau OODD 84 5 0 12 May 2022
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis Sho Sonoda Isao Ishikawa Masahiro Ikeda 60 15 0 03 Mar 2022
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets Xia Wei Aldo A. Faisal Moritz Grosse-Wentrup Alexandre Gramfort Sylvain Chevallier ... Stephen M. Gordon Vernon J. Lawhern Maciej Śliwowski Vincent Rouanne Piotr Tempczyk OOD 55 24 0 14 Feb 2022
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification Ce Ju Cuntai Guan 49 58 0 05 Feb 2022
Riemannian Local Mechanism for SPD Neural Networks Ziheng Chen Tianyang Xu Xiaojun Wu Rui Wang Zhiwu Huang J. Kittler 77 17 0 25 Jan 2022
Deep Optimal Transport for Domain Adaptation on SPD Manifolds Ce Ju Cuntai Guan 142 3 0 15 Jan 2022
Deep Efficient Continuous Manifold Learning for Time Series Modeling Seungwoo Jeong Wonjun Ko A. Mulyadi Heung-Il Suk AI4TS 85 7 0 03 Dec 2021
GeomNet: A Neural Network Based on Riemannian Geometries of SPD Matrix Space and Cholesky Space for 3D Skeleton-Based Interaction Recognition X. Nguyen 3DH 48 33 0 25 Nov 2021
Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices F. López Beatrice Pozzetti Steve J. Trettel Michael Strube Anna Wienhard 72 17 0 26 Oct 2021
Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging Benoit Anctil-Robitaille Antoine Théberge Pierre-Marc Jodoin Maxime Descoteaux Christian Desrosiers H. Lombaert MedIm DiffM 26 3 0 09 Aug 2021
cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the Elliptope Gautier Marti Victor Goubet Frank Nielsen 52 6 0 22 Jul 2021
Neural Architecture Search of SPD Manifold Networks R. Sukthanker Zhiwu Huang Suryansh Kumar Erik Goron Endsjo Yan Wu Luc Van Gool 93 14 0 27 Oct 2020
Normalization Techniques in Training DNNs: Methodology, Analysis and Application Lei Huang Jie Qin Yi Zhou Fan Zhu Li Liu Ling Shao AI4CE 176 272 0 27 Sep 2020
Partial Trace Regression and Low-Rank Kraus Decomposition Hachem Kadri Stéphane Ayache Riikka Huusari A. Rakotomamonjy L. Ralaivola 136 4 0 02 Jul 2020
Geoopt: Riemannian Optimization in PyTorch Max Kochurov R. Karimov Sergei Kozlukov 92 126 0 06 May 2020
ManifoldNorm: Extending normalizations on Riemannian Manifolds Rudrasis Chakraborty 25 11 0 30 Mar 2020
MVC-Net: A Convolutional Neural Network Architecture for Manifold-Valued Images With Applications Jose J. Bouza Chun-Hao Yang David E Vaillancourt B. Vemuri 48 4 0 02 Mar 2020
Differentiating through the Fréchet Mean Aaron Lou Isay Katsman Qingxuan Jiang Serge J. Belongie Ser-Nam Lim Christopher De Sa DRL 158 64 0 29 Feb 2020