Stochastic gradient descent on Riemannian manifolds

Stochastic gradient descent on Riemannian manifolds

22 November 2011

Silvere Bonnabel

Papers citing "Stochastic gradient descent on Riemannian manifolds"

8 / 8 papers shown

Title
Hyperspherical Normalization for Scalable Deep Reinforcement Learning Hojoon Lee Youngdo Lee Takuma Seno Donghu Kim Peter Stone Jaegul Choo 88 2 0 21 Feb 2025
Neural Network Matrix Product Operator: A Multi-Dimensionally Integrable Machine Learning Potential Kentaro Hino Yuki Kurashige 103 0 0 31 Oct 2024
Product Manifold Representations for Learning on Biological Pathways Daniel McNeela Frederic Sala A. Gitter GNN 87 2 0 27 Jan 2024
Auto-Encoding Goodness of Fit A. Palmer Zhiyi Chi Derek Aguiar J. Bi 51 1 0 12 Oct 2022
Hyperbolic Graph Convolutional Neural Networks Ines Chami Rex Ying Christopher Ré J. Leskovec GNN 50 637 0 28 Oct 2019
Approximate Bayesian inference as a gauge theory B. Sengupta Karl J. Friston 28 132 0 17 May 2017
Riemannian stochastic variance reduced gradient algorithm with retraction and vector transport Hiroyuki Sato Hiroyuki Kasai Bamdev Mishra 94 58 0 18 Feb 2017
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach Gilles Meyer Silvere Bonnabel R. Sepulchre 40 89 0 07 Jun 2010