Trivializations for Gradient-Based Optimization on Manifolds

20 September 2019

Papers citing "Trivializations for Gradient-Based Optimization on Manifolds"

25 / 25 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 46 0 0 26 Apr 2025
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series Byoungwoo Park Hyungi Lee Juho Lee AI4TS 46 0 0 08 Oct 2024
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups Zakhar Shumaylov Peter Zaika James Rowbottom Ferdia Sherry Melanie Weber Carola-Bibiane Schönlieb 41 2 0 03 Oct 2024
Neural Controlled Differential Equations with Quantum Hidden Evolutions Lingyi Yang Zhen Shao 29 0 0 30 Apr 2024
A survey of manifold learning and its applications for multimedia Hannes Fassold 42 1 0 08 Sep 2023
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation Haoqi Wang Zhizhong Li Wayne Zhang 28 2 0 03 Aug 2023
RAYEN: Imposition of Hard Convex Constraints on Neural Networks J. Tordesillas Jonathan P. How Marco Hutter 32 11 0 17 Jul 2023
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback N. Benjamin Erichson S. H. Lim Michael W. Mahoney 26 6 0 01 Dec 2022
Multi-View Independent Component Analysis with Shared and Individual Sources T. Pandeva Patrick Forré CML 15 5 0 05 Oct 2022
Random orthogonal additive filters: a solution to the vanishing/exploding gradient of deep neural networks Andrea Ceni ODL 25 3 0 03 Oct 2022
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs Fanchen Bu D. Chang 28 6 0 12 May 2022
Path Development Network with Finite-dimensional Lie Group Representation Han Lou Siran Li Hao Ni 18 7 0 02 Apr 2022
O-ViT: Orthogonal Vision Transformer Yanhong Fei Yingjie Liu Xian Wei Mingsong Chen ViT 13 8 0 28 Jan 2022
Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design Xiran Fan Chun-Hao Yang B. Vemuri 37 18 0 03 Dec 2021
Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing Bing Han Cheng Wang Kaushik Roy 34 7 0 14 Sep 2021
Coordinate descent on the orthogonal group for recurrent neural network training E. Massart V. Abrol 37 10 0 30 Jul 2021
RotoGrad: Gradient Homogenization in Multitask Learning Adrián Javaloy Isabel Valera 24 86 0 03 Mar 2021
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies T. Konstantin Rusch Siddhartha Mishra 27 89 0 02 Oct 2020
Sampling using $SU(N)$ gauge equivariant flows D. Boyda G. Kanwar S. Racanière Danilo Jimenez Rezende M. S. Albergo Kyle Cranmer D. Hackett P. Shanahan 31 127 0 12 Aug 2020
Lipschitz Recurrent Neural Networks N. Benjamin Erichson Omri Azencot A. Queiruga Liam Hodgkinson Michael W. Mahoney 30 107 0 22 Jun 2020
Neural Manifold Ordinary Differential Equations Aaron Lou Derek Lim Isay Katsman Leo Huang Qingxuan Jiang Ser-Nam Lim Christopher De Sa BDL AI4CE 23 79 0 18 Jun 2020
Orthogonal Over-Parameterized Training Weiyang Liu Rongmei Lin Zhen Liu James M. Rehg Liam Paull Li Xiong Le Song Adrian Weller 32 41 0 09 Apr 2020
Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs Matthew L. Leavitt Ari S. Morcos 58 33 0 03 Mar 2020
Differentiating through the Fréchet Mean Aaron Lou Isay Katsman Qingxuan Jiang Serge J. Belongie Ser-Nam Lim Christopher De Sa DRL 26 61 0 29 Feb 2020
Fine-grained Optimization of Deep Neural Networks Mete Ozay ODL 14 1 0 22 May 2019