Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections

1 December 2016

Papers citing "Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections"

27 / 27 papers shown

Title
Compact Recurrent Transformer with Persistent Memory Edison Mucllari Z. Daniels David C. Zhang Qiang Ye CLL VLM 51 0 0 02 May 2025
HadamRNN: Binary and Sparse Ternary Orthogonal RNNs Armand Foucault Franck Mamalet François Malgouyres MQ 74 0 0 28 Jan 2025
A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold Yanhong Fei Xian Wei Yingjie Liu Zhengyu Li Mingsong Chen 28 6 0 16 Feb 2023
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs Fanchen Bu D. Chang 28 6 0 12 May 2022
projUNN: efficient method for training deep networks with unitary matrices B. Kiani Randall Balestriero Yann LeCun S. Lloyd 43 32 0 10 Mar 2022
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs Cristian Bodnar Francesco Di Giovanni B. Chamberlain Pietro Lio Michael M. Bronstein 32 170 0 09 Feb 2022
Stable Long-Term Recurrent Video Super-Resolution Benjamin Naoto Chiche Arnaud Woiselle J. Frontera-Pons Jean-Luc Starck SupR 30 6 0 16 Dec 2021
Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition H. Sahbi GNN 23 27 0 06 Dec 2021
On the Stochastic Stability of Deep Markov Models Ján Drgoňa Sayak Mukherjee Jiaxin Zhang Frank Liu M. Halappanavar BDL 25 5 0 08 Nov 2021
Heavy Ball Neural Ordinary Differential Equations Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 38 56 0 10 Oct 2021
Acceleration Method for Learning Fine-Layered Optical Neural Networks K. Aoyama H. Sawada 27 1 0 01 Sep 2021
Coordinate descent on the orthogonal group for recurrent neural network training E. Massart V. Abrol 34 10 0 30 Jul 2021
A Universal Law of Robustness via Isoperimetry Sébastien Bubeck Mark Sellke 13 213 0 26 May 2021
Physics-Informed Neural State Space Models via Learning and Evolution Elliott Skomski Ján Drgoňa Aaron Tuor PINN AI4CE 27 9 0 26 Nov 2020
Dissipative Deep Neural Dynamical Systems Ján Drgoňa Soumya Vasisht Aaron Tuor D. Vrabie 21 7 0 26 Nov 2020
Lipschitz Recurrent Neural Networks N. Benjamin Erichson Omri Azencot A. Queiruga Liam Hodgkinson Michael W. Mahoney 30 107 0 22 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
Concept Whitening for Interpretable Image Recognition Zhi Chen Yijie Bei Cynthia Rudin FAtt 31 314 0 05 Feb 2020
Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability Max Revay I. Manchester 6 43 0 22 Dec 2019
Compressing RNNs for IoT devices by 15-38x using Kronecker Products Urmish Thakker Jesse G. Beu Dibakar Gope Chu Zhou Igor Fedorov Ganesh S. Dasika Matthew Mattina 21 36 0 07 Jun 2019
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group Mario Lezcano Casado David Martínez-Rubio 21 194 0 24 Jan 2019
How Robust are Deep Neural Networks? B. Sengupta Karl J. Friston OOD 25 31 0 30 Apr 2018
Orthogonal Recurrent Neural Networks with Scaled Cayley Transform Kyle E. Helfrich Devin Willmott Q. Ye 45 128 0 29 Jul 2017
Gated Orthogonal Recurrent Units: On Learning to Forget Li Jing Çağlar Gülçehre J. Peurifoy Yichen Shen Max Tegmark Marin Soljacic Yoshua Bengio 35 126 0 08 Jun 2017
Kronecker Recurrent Units C. Jose Moustapha Cissé F. Fleuret ODL 24 45 0 29 May 2017
On orthogonality and learning recurrent networks with long term dependencies Eugene Vorontsov C. Trabelsi Samuel Kadoury C. Pal ODL 33 238 0 31 Jan 2017
Learning Unitary Operators with Help From u(n) Stephanie L. Hyland Gunnar Rätsch 97 41 0 17 Jul 2016