Directed Graph Embeddings in Pseudo-Riemannian Manifolds

16 June 2021

Papers citing "Directed Graph Embeddings in Pseudo-Riemannian Manifolds"

9 / 9 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
A survey of manifold learning and its applications for multimedia Hannes Fassold 42 1 0 08 Sep 2023
Pseudo-Riemannian Embedding Models for Multi-Relational Graph Representations Saee Paliwal Angus Brayne Benedek Fabian Maciej Wiatrak Aaron Sim 16 0 0 02 Dec 2022
Ultrahyperbolic Knowledge Graph Embeddings Bo Xiong Shichao Zhu M. Nayyeri Chengjin Xu Shirui Pan Chuan Zhou Steffen Staab 16 31 0 01 Jun 2022
Heterogeneous manifolds for curvature-aware graph embedding Francesco Di Giovanni Giulia Luise M. Bronstein 64 23 0 02 Feb 2022
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation Learning Honglu Zhou Advith Chegu Samuel S. Sohn Zuohui Fu Gerard de Melo Mubbasir Kapadia 37 6 0 22 Dec 2021
Pseudo-Euclidean Attract-Repel Embeddings for Undirected Graphs A. Peysakhovich Anna Klimovskaia Susmel Léon Bottou GNN 27 0 0 17 Jun 2021
Pseudo-Riemannian Graph Convolutional Networks Bo Xiong Shichao Zhu Nico Potyka Shirui Pan Chuan Zhou Steffen Staab GNN 38 28 0 06 Jun 2021
MagNet: A Neural Network for Directed Graphs Xitong Zhang Yixuan He Nathan Brugnone Michael Perlmutter M. Hirn 21 124 0 22 Feb 2021