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Editors: Guy Wolf, Smita Krishnaswamy
Revisiting Graph Homophily Measures
; Proceedings of the Third Learning on Graphs Conference, PMLR 269:1:1-1:22
UnRavL: A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs
Tamara Cucumides, Daniel Daza, Pablo Barcelo, Michael Cochez, Floris Geerts, Juan L Reutter, Miguel Romero Orth; Proceedings of the Third Learning on Graphs Conference, PMLR 269:2:1-2:23
Towards a General Recipe for Combinatorial Optimization With Multi-Filter GNNs
Frederik Wenkel, Semih Cantürk, Stefan Horoi, Michael Perlmutter, Guy Wolf; Proceedings of the Third Learning on Graphs Conference, PMLR 269:3:1-3:20
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Decomposing Force Fields as Flows on Graphs Reconstructed From Stochastic Trajectories
Ramón Dineth Nartallo-Kaluarachchi, Paul Expert, David Beers, Alexander Strang, Morten L Kringelbach, Renaud Lambiotte, Alain Goriely; Proceedings of the Third Learning on Graphs Conference, PMLR 269:4:1-4:26
What Do GNNs Actually Learn? Towards Understanding Their Representations
Giannis Nikolentzos, Michail Chatzianastasis, Michalis Vazirgiannis; Proceedings of the Third Learning on Graphs Conference, PMLR 269:5:1-5:21
Ising on the Graph: Task-Specific Graph Subsampling via the Ising Model
Maria Bånkestad, Jennifer R. Andersson, Sebastian Mair, Jens Sjölund; Proceedings of the Third Learning on Graphs Conference, PMLR 269:6:1-6:29
Reinforcement Learning Discovers Efficient Decentralized Graph Path Search Strategies
Alexei Pisacane, Victor-Alexandru Darvariu, Mirco Musolesi; Proceedings of the Third Learning on Graphs Conference, PMLR 269:7:1-7:14
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A Spectral Framework for Tracking Communities in Evolving Networks
Jacob Hume, Laura Balzano; Proceedings of the Third Learning on Graphs Conference, PMLR 269:9:1-9:34
Simple GNNs With Low Rank Non-Parametric Aggregators
Luciano Vinas, Arash A. Amini; Proceedings of the Third Learning on Graphs Conference, PMLR 269:10:1-10:11
Edge-Splitting MLP: Node Classification on Homophilic and Heterophilic Graphs Without Message Passing
Matthias Kohn, Marcel Hoffmann, Ansgar Scherp; Proceedings of the Third Learning on Graphs Conference, PMLR 269:11:1-11:21
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TRIX: A More Expressive Model for Zero-Shot Domain Transfer in Knowledge Graphs
Yucheng Zhang, Beatrice Bevilacqua, Mikhail Galkin, Bruno Ribeiro; Proceedings of the Third Learning on Graphs Conference, PMLR 269:12:1-12:28
Asymptotic Generalization Error of a Single-Layer Graph Convolutional Network
O Duranthon, Lenka Zdeborova; Proceedings of the Third Learning on Graphs Conference, PMLR 269:13:1-13:27
Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph
Andreas Roth, Franka Bause, Nils Morten Kriege, Thomas Liebig; Proceedings of the Third Learning on Graphs Conference, PMLR 269:14:1-14:24
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xAI-Drop: Don’t Use What You Cannot Explain
Vincenzo Marco De Luca, Antonio Longa, Pietro Lio, Andrea Passerini; Proceedings of the Third Learning on Graphs Conference, PMLR 269:16:1-16:22
Understanding Feature/Structure Interplay in Graph Neural Networks
Diana Gomes, Ann Nowe, Peter Vrancx; Proceedings of the Third Learning on Graphs Conference, PMLR 269:17:1-17:15
Knowledge Graph Preference Contrastive Learning for Recommendation
Junze Zhu, Zhongyi Hu, Fan Zhang; Proceedings of the Third Learning on Graphs Conference, PMLR 269:18:1-18:15
DF-GNN: Dynamic Fusion Framework for Attention Graph Neural Networks on GPUs
Jiahui Liu, Zhenkun Cai, Zhiyong Chen, Minjie Wang; Proceedings of the Third Learning on Graphs Conference, PMLR 269:19:1-19:13
GraTeD-MLP: Efficient Node Classification via Graph Transformer Distillation to MLP
Sarthak Malik, Aditi Rai, Ram Ganesh V, Himank Sehgal, Akshay Sethi, Aakarsh Malhotra; Proceedings of the Third Learning on Graphs Conference, PMLR 269:20:1-20:15
Optimal Performance of Graph Convolutional Networks on the Contextual Stochastic Block Model
Guillaume Dalle, Patrick Thiran; Proceedings of the Third Learning on Graphs Conference, PMLR 269:21:1-21:17
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Leveraging Temporal Graph Networks Using Module Decoupling
Or Feldman, Chaim Baskin; Proceedings of the Third Learning on Graphs Conference, PMLR 269:22:1-22:19
Do We Really Need Complicated Graph Learning Models? – A Simple but Effective Baseline
Kaan Sancak, Muhammed Fatih Balin, Umit Catalyurek; Proceedings of the Third Learning on Graphs Conference, PMLR 269:23:1-23:19
A Pure Transformer Pretraining Framework on Text-Attributed Graphs
Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu; Proceedings of the Third Learning on Graphs Conference, PMLR 269:24:1-24:18
Hyperbolic Kernel Convolution: A Generic Framework
Eric Qu, Lige Zhang, Habib Debaya, Yue Wu, Dongmian Zou; Proceedings of the Third Learning on Graphs Conference, PMLR 269:25:1-25:25
Faster Optimization on Sparse Graphs via Neural Reparametrization
Csaba Both, Nima Dehmamy, Jianzhi Long, Rose Yu; Proceedings of the Third Learning on Graphs Conference, PMLR 269:26:1-26:21
NP-NDS: A Nature-Powered Nonlinear Dynamical System for Power Grid Forecasting
Chunshu Wu, Ruibing Song, Chuan Liu, Yuqing Wang, Yousu Chen, Ang Li, Dongfang Liu, Ying Nian Wu, Michael Huang, Tong Geng; Proceedings of the Third Learning on Graphs Conference, PMLR 269:27:1-27:14
UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs
Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi; Proceedings of the Third Learning on Graphs Conference, PMLR 269:28:1-28:16
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Flexible Diffusion Scopes With Parameterized Laplacian for Heterophilic Graph Learning
Qincheng Lu, Jiaqi Zhu, Sitao Luan, Xiao-Wen Chang; Proceedings of the Third Learning on Graphs Conference, PMLR 269:29:1-29:20
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Oversquashing in Hypergraph Neural Networks
Naganand Yadati; Proceedings of the Third Learning on Graphs Conference, PMLR 269:30:1-30:16
Smoothed Graph Contrastive Learning via Seamless Proximity Integration
Maysam Behmanesh, Maks Ovsjanikov; Proceedings of the Third Learning on Graphs Conference, PMLR 269:31:1-31:26
Stochastic Experience-Replay for Graph Continual Learning
Arnab Kumar Mondal, Jay Nandy, Manohar Kaul, Mahesh Chandran; Proceedings of the Third Learning on Graphs Conference, PMLR 269:32:1-32:16
Enhancing Topological Dependencies in Spatio-Temporal Graphs With Cycle Message Passing Blocks
Minho Lee, Yun Young Choi, Sun Woo Park, Seunghwan Lee, Joohwan Ko, Jaeyoung Hong; Proceedings of the Third Learning on Graphs Conference, PMLR 269:33:1-33:17
Matrix Completion With Hypergraphs: Sharp Thresholds and Efficient Algorithms
Zhongtian Ma, Qiaosheng Zhang, Zhen Wang; Proceedings of the Third Learning on Graphs Conference, PMLR 269:34:1-34:30
Do Neural Scaling Laws Exist on Graph Self-Supervised Learning?
Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma; Proceedings of the Third Learning on Graphs Conference, PMLR 269:35:1-35:24
Sub-Graph Based Diffusion Model for Link Prediction
Hang Li, Wei Jin, Geri Skenderi, Harry Shomer, Wenzhuo Tang, Wenqi Fan, Jiliang Tang; Proceedings of the Third Learning on Graphs Conference, PMLR 269:36:1-36:17
Multi-Scale High-Resolution Logarithmic Grapher Module for Efficient Vision GNNs
Mustafa Munir, Alex Zhang, Radu Marculescu; Proceedings of the Third Learning on Graphs Conference, PMLR 269:37:1-37:13
CrysAtom: Distributed Representation of Atoms for Crystal Property Prediction
Shrimon Mukherjee, Madhusudan Ghosh, Partha Basuchowdhuri; Proceedings of the Third Learning on Graphs Conference, PMLR 269:38:1-38:19
T-Gae: Transferable Graph Autoencoder for Network Alignment
Jiashu He, Charilaos Kanatsoulis, Alejandro Ribeiro; Proceedings of the Third Learning on Graphs Conference, PMLR 269:40:1-40:25
Motif-Aware Attribute Masking for Molecular Graph Pre-Training
Eric Inae, Gang Liu, Meng Jiang; Proceedings of the Third Learning on Graphs Conference, PMLR 269:41:1-41:15
On the Expressivity of Persistent Homology in Graph Learning
Rubén Ballester, Bastian Rieck; Proceedings of the Third Learning on Graphs Conference, PMLR 269:42:1-42:31
Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models
Kay Liu, Hengrui Zhang, Ziqing Hu, Fangxin Wang, Philip S. Yu; Proceedings of the Third Learning on Graphs Conference, PMLR 269:43:1-43:20
Towards Neural Scaling Laws on Graphs
Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang; Proceedings of the Third Learning on Graphs Conference, PMLR 269:44:1-44:22
CliquePH: Higher-Order Information for Graph Neural Networks Through Persistent Homology on Clique Graphs
Davide Buffelli, Farzin Soleymani, Bastian Rieck; Proceedings of the Third Learning on Graphs Conference, PMLR 269:45:1-45:17
Lifted Model Construction Without Normalisation: A Vectorised Approach to Exploit Symmetries in Factor Graphs
Malte Luttermann, Ralf Möller, Marcel Gehrke; Proceedings of the Third Learning on Graphs Conference, PMLR 269:46:1-46:17
Dynamic Representations of Global Crises: A Temporal Knowledge Graph for Conflicts, Trade and Value Networks
Julia Gastinger, Timo Sztyler, Nils Steinert, Sabine Gründer-Fahrer, Michael Martin, Anett Schuelke, Heiner Stuckenschmidt; Proceedings of the Third Learning on Graphs Conference, PMLR 269:47:1-47:22
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