Graph Positional Encoding

Follow this topic Ask about this topic

Latest papers

15 papers4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Path Laplacian Encodings for Directed Graphs
Oct 3, 2026Lydia Mezrag, Semih Cantürk, Michael Perlmutter +2Graph Positional Encoding Positional Encoding
Université de Montréal · Mila – Quebec AI Institute · Boise State University +1
Higher-Order Positional Encodings for Graph Representation Learning
Oct 1, 2026Caleb Stam, Aagrim Hoysal, Sanjukta KrishnagopalGraph Representation Learning Positional Encoding
University of California, Santa Barbara
Retargeting Motions to Diverse Skeletons via Learnable Flattening
Sep 29, 2026Kia-Jüng Yang, Fabian H. Sinz, Paweł A. PierzchlewiczGraph Positional Encoding Zero-Shot Learning
Institute of Computer Science, University of Göttingen · Campus Institute Data Science, University Göttingen · Pantomim P.S.A
Analytic-Walk Rotary Positional Encodings for Graphs
Sep 26, 2026Jiaqing Xie, Yuxin Wang, Xipeng QiuGraph Positional Encoding Rotary Positional Embeddings
Shanghai Innovation Institute · Fudan University
Converse and Collision-Based Achievability for Node Localization with Hybrid Distance-Spectral Graph Positional Encodings
Aug 31, 2026Zimo Yan, Yifan Li, Hao Li +4Representation Identifiability Positional Encoding
National University of Defense Technology, Changsha, China · Wuhan University, Wuhan, China
Multi-Granularity Position Embedding of Graphs via Granular-Ball for Link Prediction
Jul 31, 2026Sen Zhao, Cheng Liu, Shuyin Xia +4Graph Positional Encoding Graph Representation Learning
Chongqing Key Laboratory of Computational Intelligence, Key Laboratory of Big Data Intelligent Computing, Key Laboratory of Cyberspace Big Data Intelligent Security, Ministry of Education, School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China · Chongqing Key Laboratory of Computational Intelligence, Key Laboratory of Big Data Intelligent Computing, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China · Chongqing Ant ConsumerFinance Co,. Ltd, Ant Group, Chongqing, 400065, China
Eigenbasis-Independent Learnable Spectral Positional Encodings for Directed Graphs via Hermitian Block Krylov Subspaces
Jul 8, 2026Jiaqing Xie, Yuxin WangPositional Encoding Spectral Methods
Fudan University
Communicability-Inspired Positional Encoding (CIPE)
Jun 24, 2026Yipeng Zhang, Zhongtian Sun, Pietro Liò +1Graph Positional Encoding Graph Representation Learning
Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore · School of Computing, University of Kent, Canterbury, Kent CT2 7NZ, UK · Department of Computer Science and Technology, University of Cambridge, 15 JJ Thomson Avenue, Cambridge CB3 0FD, UK
Understanding Truncated Positional Encodings for Graph Neural Networks
Jun 11, 2026James Flora, Mitchell Black, Weng-Keen Wong +1GNN Expressivity Positional Encoding
School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, Oregon, USA · Halıcıoğlu Data Science Institute, University of California San Diego, San Diego, California, USA.
When Do Graph Foundation Models Transfer? A Data-Centric Theory
May 28, 2026Jiajun Zhu, Ying Chen, Peihao Wang +4Graph Positional Encoding Graphon Theory
University of Texas at Austin · Arizona State University · Georgia Institute of Technology
Rethinking Graph Convolution for 2D-to-3D Hand Pose Lifting
May 13, 2026Chanyoung Kim, Donghyun Kim, Dong-Hyun Sim +2Graph Positional Encoding Graph Attention Networks
Emory University · Yonsei University · WHATs Lab
Rethinking Positional Encoding for Neural Vehicle Routing
May 12, 2026Chuanbo Hua, Federico Berto, Andre Hottung +8Vehicle Routing Positional Encoding
KAIST · Radical Numerics · Bielefeld University +3
Size-Transferability of Graph Transformers with Convolutional Positional Encodings
Feb 16, 2026Javier Porras-Valenzuela, Zhiyang Wang, Teresa Shang +2Graph Positional Encoding Graph Transformer
Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA · Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
Rotary Position Encodings for Graphs
Sep 26, 2025Isaac Reid, Arijit Sehanobish, Cederik Höfs +7Graph Positional Encoding Rotary Positional Embeddings
University of Cambridge · Google DeepMind · Independent Researcher +3
Teaching MLP More Graph Information: A Three-stage Multitask Knowledge Distillation Framework
Mar 2, 2024Junxian Li, Bin Shi, Erfei Cui +2Graph Positional Encoding Knowledge Distillation
Xi’an Jiaotong University · Arizona State University, Tempe, USA · Tongji University, Shanghai, China

Oct 3, 2026J/K move · Enter open · S save

Path Laplacian Encodings for Directed Graphs

Lydia Mezrag, Semih Cantürk, Michael Perlmutter, Bastian Rieck+1

Université de Montréal · Mila – Quebec AI Institute · Boise State University+1

Graph Positional Encoding Positional Encoding Graph Neural Networks

Open paper AskPDF arXiv

Directed graphs naturally model many real-world systems in which interactions are asymmetric, such as citation networks, web graphs, and information-flow networks. However, graph learning methods commonly rely on message passing with symmetrized graph representations or positional encodings that only partially exploit edge directionality. We introduce PathLapPE, a novel spectral positional encoding (PE) derived from the path Laplacian on directed graphs. PathLapPE provides node- and edge-level features that encode directional higher-order structure and can be incorporated into standard graph learning architectures. Empirical results on node- and graph-level benchmark tasks show that PathLapPE yields consistent improvements across several architectures, especially when combined with direction-aware message passing. Compared with magnetic Laplacian positional encodings, a widely studied spectral positional encoding for directed graphs, PathLapPE does not require additional fine-tuning of directionality hyperparameters while offering competitive runtime and performance.