Heterogeneous manifolds for curvature-aware graph embedding

2 February 2022

Papers citing "Heterogeneous manifolds for curvature-aware graph embedding"

19 / 19 papers shown

Title
Neural Spacetimes for DAG Representation Learning Haitz Sáez de Ocáriz Borde Anastasis Kratsios Marc T. Law Xiaowen Dong Michael Bronstein CML 46 0 0 25 Aug 2024
Product Manifold Representations for Learning on Biological Pathways Daniel McNeela Frederic Sala A. Gitter GNN 69 2 0 27 Jan 2024
DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing Li Sun Zhenhao Huang Hua Wu Junda Ye Hao Peng Zhengtao Yu Philip S. Yu 31 11 0 23 Jan 2024
Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning Li Sun Zhenhao Huang Zixi Wang Feiyang Wang Hao Peng Philip Yu 29 16 0 02 Jan 2024
Normed Spaces for Graph Embedding Diaaeldin Taha Wei-Ye Zhao J. M. Riestenberg Michael Strube 45 1 0 03 Dec 2023
Improving embedding of graphs with missing data by soft manifolds Andrea Marinoni Pietro Lio' Alessandro Barp Christian Jutten M. Girolami 21 0 0 29 Nov 2023
Over-Squashing in Riemannian Graph Neural Networks Julia Balla 25 0 0 27 Nov 2023
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries Haitz Sáez de Ocáriz Borde Anastasis Kratsios 37 4 0 23 Oct 2023
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning Sungjun Cho Seunghyuk Cho Sungwoo Park Hankook Lee Ho Hin Lee Moontae Lee 29 6 0 08 Sep 2023
Capacity Bounds for Hyperbolic Neural Network Representations of Latent Tree Structures Anastasis Kratsios Rui Hong Haitz Sáez de Ocáriz Borde 27 4 0 18 Aug 2023
Improving Heterogeneous Graph Learning with Weighted Mixed-Curvature Product Manifold Tuc Nguyen-Van Dung D. Le The-Anh Ta 38 1 0 10 Jul 2023
Contrastive Graph Clustering in Curvature Spaces Li Sun Feiyang Wang Junda Ye Hao Peng Philip S. Yu 24 17 0 05 May 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology Francesco Di Giovanni Lorenzo Giusti Federico Barbero Giulia Luise Pietro Lio' Michael M. Bronstein 38 112 0 06 Feb 2023
Latent Graph Inference using Product Manifolds Haitz Sáez de Ocáriz Borde Anees Kazi Federico Barbero Pietro Lio' BDL 32 18 0 26 Nov 2022
Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifolds Noémie Jaquier Leonel Rozo Miguel González-Duque Viacheslav Borovitskiy Tamim Asfour 43 7 0 04 Oct 2022
Small Transformers Compute Universal Metric Embeddings Anastasis Kratsios Valentin Debarnot Ivan Dokmanić 56 11 0 14 Sep 2022
Tuning the Geometry of Graph Neural Networks Sowon Jeong Claire Donnat AI4CE 45 1 0 12 Jul 2022
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,104 0 27 Apr 2021
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 250 3,236 0 24 Nov 2016