Riemannian Adaptive Optimization Methods

1 October 2018

Papers citing "Riemannian Adaptive Optimization Methods"

50 / 54 papers shown

Title
Online Functional Principal Component Analysis on a Multidimensional Domain Muye Nanshan Nan Zhang Jiguo Cao 23 0 0 04 May 2025
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
Learning Isometric Embeddings of Road Networks using Multidimensional Scaling Juan Carlos Climent Pardo 42 0 0 24 Apr 2025
LGIN: Defining an Approximately Powerful Hyperbolic GNN Srinitish Srinivasan Omkumar CU AI4CE 45 0 0 31 Mar 2025
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Xing Hu Yuan Cheng Dawei Yang Zukang Xu Zhihang Yuan Jiangyong Yu Chen Xu Zhe Jiang Sifan Zhou MQ 41 6 0 23 Jan 2025
Neural Network Matrix Product Operator: A Multi-Dimensionally Integrable Machine Learning Potential Kentaro Hino Yuki Kurashige 34 0 0 31 Oct 2024
On Probabilistic Pullback Metrics for Latent Hyperbolic Manifolds Luis Augenstein Noémie Jaquier Tamim Asfour Leonel Rozo 26 0 0 28 Oct 2024
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics Katharina Friedl Noémie Jaquier Jens Lundell Tamim Asfour Danica Kragic AI4CE 28 0 0 24 Oct 2024
Compositional Entailment Learning for Hyperbolic Vision-Language Models Avik Pal Max van Spengler Guido Maria DÁmely di Melendugno Alessandro Flaborea Fabio Galasso Pascal Mettes CoGe 48 5 0 09 Oct 2024
HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean Space Jacob Fein-Ashley Ethan Feng Minh Pham 32 3 0 25 Sep 2024
Geometry Aware Meta-Learning Neural Network for Joint Phase and Precoder Optimization in RIS Dahlia Devapriya Sheetal Kalyani 25 0 0 17 Sep 2024
Mixed-Curvature Decision Trees and Random Forests Philippe Chlenski Quentin Chu I. Pe’er 36 1 0 07 Jun 2024
Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks Jing Gu Dongmian Zou 37 3 0 06 Mar 2024
Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein Hugues van Assel Cédric Vincent-Cuaz Nicolas Courty Rémi Flamary Pascal Frossard Titouan Vayer 26 4 0 03 Feb 2024
Product Manifold Representations for Learning on Biological Pathways Daniel McNeela Frederic Sala A. Gitter GNN 72 2 0 27 Jan 2024
GaussianHead: High-fidelity Head Avatars with Learnable Gaussian Derivation Jie Wang Jiucheng Xie Xianyan Li Feng Xu Chi-Man Pun Hao Gao 3DGS 41 23 0 04 Dec 2023
A survey of manifold learning and its applications for multimedia Hannes Fassold 42 1 0 08 Sep 2023
Warped geometric information on the optimisation of Euclidean functions M. Hartmann Bernardo Williams Hanlin Yu Mark Girolami Alessandro Barp Arto Klami 24 2 0 16 Aug 2023
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation Haoqi Wang Zhizhong Li Wayne Zhang 23 2 0 03 Aug 2023
Hyperbolic Representation Learning: Revisiting and Advancing Menglin Yang Min Zhou Rex Ying Yankai Chen Irwin King 40 20 0 15 Jun 2023
Hyperbolic Convolution via Kernel Point Aggregation Eric Qu Dongmian Zou 45 3 0 15 Jun 2023
Fully Hyperbolic Convolutional Neural Networks for Computer Vision Ahmad Bdeir Kristian Schwethelm Niels Landwehr 41 10 0 28 Mar 2023
Faster Riemannian Newton-type Optimization by Subsampling and Cubic Regularization Yian Deng Tingting Mu 21 1 0 22 Feb 2023
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
Hierarchical Explanations for Video Action Recognition Sadaf Gulshad Teng Long Nanne van Noord FAtt 29 6 0 01 Jan 2023
Bayesian Learning for Neural Networks: an algorithmic survey M. Magris Alexandros Iosifidis BDL DRL 35 68 0 21 Nov 2022
Auto-Encoding Goodness of Fit A. Palmer Zhiyi Chi Derek Aguiar J. Bi 41 1 0 12 Oct 2022
Hyperbolic Deep Reinforcement Learning Edoardo Cetin B. Chamberlain Michael M. Bronstein Jonathan J. Hunt 43 21 0 04 Oct 2022
Rethinking the compositionality of point clouds through regularization in the hyperbolic space Antonio Montanaro D. Valsesia E. Magli 3DPC 46 31 0 21 Sep 2022
Text Enriched Sparse Hyperbolic Graph Convolutional Networks Nurendra Choudhary Nikhil S. Rao Karthik Subbian Chandan K. Reddy 28 0 0 06 Jul 2022
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG Reinmar J. Kobler J. Hirayama Qibin Zhao M. Kawanabe 19 53 0 02 Jun 2022
Heterogeneous manifolds for curvature-aware graph embedding Francesco Di Giovanni Giulia Luise M. Bronstein 64 23 0 02 Feb 2022
GeomNet: A Neural Network Based on Riemannian Geometries of SPD Matrix Space and Cholesky Space for 3D Skeleton-Based Interaction Recognition X. Nguyen 3DH 19 33 0 25 Nov 2021
Grassmannian learning mutual subspace method for image set recognition L. S. Souza Naoya Sogi B. Gatto Takumi Kobayashi Kazuhiro Fukui 19 11 0 08 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 39 17 0 26 Oct 2021
Transductive Few-Shot Classification on the Oblique Manifold Guodong Qi Huimin Yu Zhaohui Lu Shuzhao Li 19 45 0 09 Aug 2021
Coordinate descent on the orthogonal group for recurrent neural network training E. Massart V. Abrol 37 10 0 30 Jul 2021
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis Zihang Meng Rudrasis Chakraborty Vikas Singh 9 9 0 08 Jun 2021
Learning the Predictability of the Future Dídac Surís Ruoshi Liu Carl Vondrick 24 71 0 01 Jan 2021
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs Nurendra Choudhary Nikhil S. Rao S. Katariya Karthik Subbian Chandan K. Reddy 16 64 0 23 Dec 2020
A Fully Hyperbolic Neural Model for Hierarchical Multi-Class Classification F. López Michael Strube 15 28 0 05 Oct 2020
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering Ines Chami Albert Gu Vaggos Chatziafratis Christopher Ré 23 95 0 01 Oct 2020
Riemannian stochastic recursive momentum method for non-convex optimization Andi Han Junbin Gao ODL 28 17 0 11 Aug 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 27 119 0 18 Jun 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 22 285 0 07 May 2020
Time Series Alignment with Global Invariances Titouan Vayer R. Tavenard Laetitia Chapel Nicolas Courty Rémi Flamary Yann Soullard AI4TS 24 16 0 10 Feb 2020
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform Jun Li Fuxin Li S. Todorovic 24 102 0 04 Feb 2020
Quaternion Equivariant Capsule Networks for 3D Point Clouds Yongheng Zhao Tolga Birdal J. E. Lenssen Emanuele Menegatti Leonidas J. Guibas Federico Tombari 3DPC 26 88 0 27 Dec 2019
Mixed-curvature Variational Autoencoders Ondrej Skopek O. Ganea Gary Bécigneul CML DRL BDL 30 101 0 19 Nov 2019
Hyperbolic Graph Neural Networks Qi Liu Maximilian Nickel Douwe Kiela AI4CE GNN 45 370 0 28 Oct 2019