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1909.02414
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Riemannian batch normalization for SPD neural networks
Neural Information Processing Systems (NeurIPS), 2019
3 September 2019
Daniel A. Brooks
Olivier Schwander
F. Barbaresco
J. Schneider
Matthieu Cord
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Papers citing
"Riemannian batch normalization for SPD neural networks"
48 / 48 papers shown
RecruitView: A Multimodal Dataset for Predicting Personality and Interview Performance for Human Resources Applications
Amit Kumar Gupta
Farhan Sheth
Hammad Shaikh
Dheeraj Kumar
Angkul Puniya
Deepak Panwar
Sandeep Chaurasia
Priya Mathur
150
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0
29 Nov 2025
DFNN: A Deep Fréchet Neural Network Framework for Learning Metric-Space-Valued Responses
Kyum Kim
Yaqing Chen
Paromita Dubey
154
1
0
20 Oct 2025
Geometric Moment Alignment for Domain Adaptation via Siegel Embeddings
Shayan Gharib
M. Hartmann
Arto Klami
165
2
0
16 Oct 2025
SPD Matrix Learning for Neuroimaging Analysis: Perspectives, Methods, and Challenges
Ce Ju
Reinmar J. Kobler
Antoine Collas
M. Kawanabe
Cuntai Guan
Bertrand Thirion
443
0
0
26 Apr 2025
Learning to Normalize on the SPD Manifold under Bures-Wasserstein Geometry
Computer Vision and Pattern Recognition (CVPR), 2025
Rui Wang
Shaocheng Jin
Ziheng Chen
Xiaoqing Luo
Rui Wang
330
4
0
01 Apr 2025
Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
Thibault de Surrel
Fabien Lotte
Sylvain Chevallier
Florian Yger
581
3
0
03 Feb 2025
SMLNet: A SPD Manifold Learning Network for Infrared and Visible Image Fusion
Huan Kang
Hui Li
Tianyang Xu
Rui Wang
Rui Wang
J. Kittler
Josef Kittler
634
1
0
16 Nov 2024
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
International Conference on Learning Representations (ICLR), 2024
Ya-Wei Eileen Lin
Ronald R. Coifman
Zhengchao Wan
Ronen Talmon
606
9
0
28 Oct 2024
Representation Learning for Regime detection in Block Hierarchical Financial Markets
Alexa Orton
Tim Gebbie
AIFin
138
0
0
14 Oct 2024
RMLR: Extending Multinomial Logistic Regression into General Geometries
Neural Information Processing Systems (NeurIPS), 2024
Ziheng Chen
Yue Song
Rui Wang
Xiaojun Wu
Andrii Zadaianchuk
276
6
0
28 Sep 2024
Classification of Buried Objects from Ground Penetrating Radar Images by using Second Order Deep Learning Models
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (IEEE JSTARS), 2024
Douba Jafuno
A. Mian
G. Ginolhac
Nickolas Stelzenmuller
294
4
0
20 Sep 2024
Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry
Ziheng Chen
Yue Song
Xiao-Jun Wu
Andrii Zadaianchuk
267
2
0
02 Jul 2024
Matrix Manifold Neural Networks++
Xuan Son Nguyen
Shuo Yang
A. Histace
371
10
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
418
1
0
10 May 2024
A Lie Group Approach to Riemannian Batch Normalization
Ziheng Chen
Yue Song
Yunmei Liu
Andrii Zadaianchuk
BDL
319
9
0
17 Mar 2024
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Improving Knowledge Distillation using Orthogonal Projections
Computer Vision and Pattern Recognition (CVPR), 2024
Roy Miles
Ismail Elezi
Jiankang Deng
383
28
0
10 Mar 2024
SPD-DDPM: Denoising Diffusion Probabilistic Models in the Symmetric Positive Definite Space
AAAI Conference on Artificial Intelligence (AAAI), 2023
Yunchen Li
Zhou Yu
Gaoqi He
Chunjiang Ge
Ke Li
Xing Sun
Shaohui Lin
DiffM
184
17
0
13 Dec 2023
Riemannian Self-Attention Mechanism for SPD Networks
Rui Wang
Xiao-Jun Wu
Hui Li
Josef Kittler
253
2
0
28 Nov 2023
Riemannian Residual Neural Networks
Isay Katsman
Eric Chen
Sidhanth Holalkere
Anna Asch
Aaron Lou
Ser-Nam Lim
Christopher De Sa
299
26
0
16 Oct 2023
Deep Geometric Learning with Monotonicity Constraints for Alzheimer's Disease Progression
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Seungwoo Jeong
Wonsik Jung
Junghyo Sohn
Heung-Il Suk
281
7
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
245
9
0
24 Jun 2023
R-Mixup: Riemannian Mixup for Biological Networks
Knowledge Discovery and Data Mining (KDD), 2023
Xuan Kan
Zimu Li
Hejie Cui
Yue Yu
Ran Xu
Shaojun Yu
Zilong Zhang
Ying Guo
Carl Yang
323
11
0
05 Jun 2023
Riemannian Multinomial Logistics Regression for SPD Neural Networks
Computer Vision and Pattern Recognition (CVPR), 2023
Ziheng Chen
Yue Song
Gaowen Liu
Ramana Rao Kompella
Xiaojun Wu
Andrii Zadaianchuk
311
8
0
18 May 2023
Building Neural Networks on Matrix Manifolds: A Gyrovector Space Approach
International Conference on Machine Learning (ICML), 2023
X. Nguyen
Shuo Yang
296
15
0
08 May 2023
Differential geometry with extreme eigenvalues in the positive semidefinite cone
SIAM Journal on Matrix Analysis and Applications (SIMAX), 2023
Cyrus Mostajeran
Nathael Da Costa
Graham W. Van Goffrier
R. Sepulchre
392
6
0
14 Apr 2023
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals
International Conference on Machine Learning (ICML), 2023
Clément Bonet
Benoit Malézieux
A. Rakotomamonjy
Lucas Drumetz
Thomas Moreau
M. Kowalski
Nicolas Courty
416
28
0
10 Mar 2023
Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective from the Time-Frequency Analysis
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Ce Ju
Cuntai Guan
416
33
0
25 Oct 2022
MAtt: A Manifold Attention Network for EEG Decoding
Neural Information Processing Systems (NeurIPS), 2022
Yue Pan
Jing-Lun Chou
Chunshan Wei
189
80
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
179
2
0
16 Jun 2022
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
Neural Information Processing Systems (NeurIPS), 2022
Reinmar J. Kobler
J. Hirayama
Qibin Zhao
M. Kawanabe
329
77
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
258
5
0
12 May 2022
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis
International Conference on Machine Learning (ICML), 2022
Sho Sonoda
Isao Ishikawa
Masahiro Ikeda
293
18
0
03 Mar 2022
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
Neural Information Processing Systems (NeurIPS), 2022
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
147
32
0
14 Feb 2022
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Ce Ju
Cuntai Guan
316
84
0
05 Feb 2022
Riemannian Local Mechanism for SPD Neural Networks
AAAI Conference on Artificial Intelligence (AAAI), 2022
Ziheng Chen
Tianyang Xu
Xiaojun Wu
Rui Wang
Zhiwu Huang
J. Kittler
348
33
0
25 Jan 2022
Deep Optimal Transport for Domain Adaptation on SPD Manifolds
Artificial Intelligence (AIJ), 2022
Ce Ju
Cuntai Guan
638
7
0
15 Jan 2022
Deep Efficient Continuous Manifold Learning for Time Series Modeling
Seungwoo Jeong
Wonjun Ko
A. Mulyadi
Heung-Il Suk
AI4TS
295
14
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
248
40
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
246
24
0
26 Oct 2021
Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging
Frontiers in Neuroimaging (FN), 2021
Benoit Anctil-Robitaille
Antoine Théberge
Pierre-Marc Jodoin
Maxime Descoteaux
Christian Desrosiers
H. Lombaert
MedIm
DiffM
245
4
0
09 Aug 2021
cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the Elliptope
International Conference on Geometric Science of Information (GSI), 2021
Gautier Marti
Victor Goubet
Frank Nielsen
261
6
0
22 Jul 2021
Neural Architecture Search of SPD Manifold Networks
International Joint Conference on Artificial Intelligence (IJCAI), 2020
R. Sukthanker
Zhiwu Huang
Suryansh Kumar
Erik Goron Endsjo
Yan Wu
Luc Van Gool
541
15
0
27 Oct 2020
Normalization Techniques in Training DNNs: Methodology, Analysis and Application
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Lei Huang
Jie Qin
Yi Zhou
Fan Zhu
Li Liu
Ling Shao
AI4CE
467
411
0
27 Sep 2020
Partial Trace Regression and Low-Rank Kraus Decomposition
Hachem Kadri
Stéphane Ayache
Riikka Huusari
A. Rakotomamonjy
L. Ralaivola
354
5
0
02 Jul 2020
Geoopt: Riemannian Optimization in PyTorch
Max Kochurov
R. Karimov
Sergei Kozlukov
495
167
0
06 May 2020
ManifoldNorm: Extending normalizations on Riemannian Manifolds
Rudrasis Chakraborty
253
15
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
262
6
0
02 Mar 2020
Differentiating through the Fréchet Mean
International Conference on Machine Learning (ICML), 2020
Aaron Lou
Isay Katsman
Qingxuan Jiang
Serge J. Belongie
Ser-Nam Lim
Christopher De Sa
DRL
420
81
0
29 Feb 2020
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