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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 231: Learning on Graphs Conference, 27-30 November 2023, Virtual

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Editors: Soledad Villar, Benjamin Chamberlain

[bib][citeproc]

Contents:

  • Preface
  • Oral Presentations
  • Poster Presentations

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Preface

The Second Learning on Graphs Conference: Preface

Soledad Villar, Benjamin Chamberlain, Yuanqi Du, Hannes St"ark, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan; Proceedings of the Second Learning on Graphs Conference, PMLR 231:i-xix

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Oral Presentations

Representing Edge Flows on Graphs via Sparse Cell Complexes

; Proceedings of the Second Learning on Graphs Conference, PMLR 231:1:1-1:22

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Meta-Path Learning for Multi-Relational Graph Neural Networks

Francesco Ferrini, Antonio Longa, Andrea Passerini, Manfred Jaeger; Proceedings of the Second Learning on Graphs Conference, PMLR 231:2:1-2:17

[abs][Download PDF][OpenReview]

Asynchronous Algorithmic Alignment With Cocycles

Andrew Joseph Dudzik, Tamara von Glehn, Razvan Pascanu, Petar Veličković; Proceedings of the Second Learning on Graphs Conference, PMLR 231:3:1-3:17

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Cycle Invariant Positional Encoding for Graph Representation Learning

Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen, Yusu Wang; Proceedings of the Second Learning on Graphs Conference, PMLR 231:4:1-4:21

[abs][Download PDF][OpenReview][Supplementary ZIP]

Recursive Algorithmic Reasoning

Jonas Jürß, Dulhan Hansaja Jayalath, Petar Veličković; Proceedings of the Second Learning on Graphs Conference, PMLR 231:5:1-5:14

[abs][Download PDF][OpenReview][Software]

On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks

Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T Schaub, Danai Koutra; Proceedings of the Second Learning on Graphs Conference, PMLR 231:6:1-6:30

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Poster Presentations

Spectral Subgraph Localization

Ama Bembua Bainson, Judith Hermanns, Petros Petsinis, Niklas Aavad, Casper Dam Larsen, Tiarnan Swayne, Amit Boyarski, Davide Mottin, Alex M. Bronstein, Panagiotis Karras; Proceedings of the Second Learning on Graphs Conference, PMLR 231:7:1-7:11

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GSCAN: Graph Stability Clustering for Applications With Noise Using Edge-Aware Excess-of-Mass

Etzion Harari, Naphtali Abudarham, Roee Litman; Proceedings of the Second Learning on Graphs Conference, PMLR 231:9:1-9:15

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Latent Space Representations of Neural Algorithmic Reasoners

Vladimir V Mirjanic, Razvan Pascanu, Petar Veličković; Proceedings of the Second Learning on Graphs Conference, PMLR 231:10:1-10:24

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Multicoated and Folded Graph Neural Networks With Strong Lottery Tickets

Jiale Yan, Hiroaki Ito, Ángel López García-Arias, Yasuyuki Okoshi, Hikari Otsuka, Kazushi Kawamura, Thiem Van Chu, Masato Motomura; Proceedings of the Second Learning on Graphs Conference, PMLR 231:11:1-11:18

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PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs

Yixuan He, Xitong Zhang, Junjie Huang, Benedek Rozemberczki, Mihai Cucuringu, Gesine Reinert; Proceedings of the Second Learning on Graphs Conference, PMLR 231:12:1-12:27

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SURF: A Generalization Benchmark for GNNs Predicting Fluid Dynamics

Stefan Künzli, Florian Grötschla, Joël Mathys, Roger Wattenhofer; Proceedings of the Second Learning on Graphs Conference, PMLR 231:13:1-13:23

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Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks

Jing Gu, Dongmian Zou; Proceedings of the Second Learning on Graphs Conference, PMLR 231:14:1-14:29

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HOT: Higher-Order Dynamic Graph Representation Learning With Efficient Transformers

Maciej Besta, Afonso Claudino Catarino, Lukas Gianinazzi, Nils Blach, Piotr Nyczyk, Hubert Niewiadomski, Torsten Hoefler; Proceedings of the Second Learning on Graphs Conference, PMLR 231:15:1-15:20

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Generalized Reasoning With Graph Neural Networks by Relational Bayesian Network Encodings

Raffaele Pojer, Andrea Passerini, Manfred Jaeger; Proceedings of the Second Learning on Graphs Conference, PMLR 231:16:1-16:12

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Non-Isotropic Persistent Homology: Leveraging the Metric Dependency of PH

Vincent Peter Grande, Michael T Schaub; Proceedings of the Second Learning on Graphs Conference, PMLR 231:17:1-17:19

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Transferable Hypergraph Neural Networks via Spectral Similarity

Mikhail Hayhoe, Hans Matthew Riess, Michael M. Zavlanos, VICTOR PRECIADO, Alejandro Ribeiro; Proceedings of the Second Learning on Graphs Conference, PMLR 231:18:1-18:23

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Mitigating Over-Smoothing and Over-Squashing Using Augmentations of Forman-Ricci Curvature

Lukas Fesser, Melanie Weber; Proceedings of the Second Learning on Graphs Conference, PMLR 231:19:1-19:28

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Interaction Models and Generalized Score Matching for Compositional Data

Shiqing Yu, Mathias Drton, Ali Shojaie; Proceedings of the Second Learning on Graphs Conference, PMLR 231:20:1-20:25

[abs][Download PDF][OpenReview][Software]

Will More Expressive Graph Neural Networks Do Better on Generative Tasks?

Xiandong Zou, Xiangyu Zhao, Pietro Lio, Yiren Zhao; Proceedings of the Second Learning on Graphs Conference, PMLR 231:21:1-21:26

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Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations

Dhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, James Noonan, Guy Wolf, Natalia Ivanova, Smita Krishnaswamy; Proceedings of the Second Learning on Graphs Conference, PMLR 231:22:1-22:21

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Intrinsically Motivated Graph Exploration Using Network Theories of Human Curiosity

Shubhankar Prashant Patankar, Mathieu Ouellet, Juan Cervino, Alejandro Ribeiro, Kieran A. Murphy, Danielle Bassett; Proceedings of the Second Learning on Graphs Conference, PMLR 231:23:1-23:15

[abs][Download PDF][OpenReview][Software][Supplementary ZIP]

EMP: Effective Multidimensional Persistence for Graph Representation Learning

Yuzhou Chen, Ignacio Segovia-Dominguez, Cuneyt Gurcan Akcora, Zhiwei Zhen, Murat Kantarcioglu, Yulia Gel, Baris Coskunuzer; Proceedings of the Second Learning on Graphs Conference, PMLR 231:24:1-24:12

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Edge Directionality Improves Learning on Heterophilic Graphs

Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein; Proceedings of the Second Learning on Graphs Conference, PMLR 231:25:1-25:27

[abs][Download PDF][OpenReview][Software][Supplementary ZIP]

A Simple Latent Variable Model for Graph Learning and Inference

Manfred Jaeger, Antonio Longa, Steve Azzolin, Oliver Schulte, Andrea Passerini; Proceedings of the Second Learning on Graphs Conference, PMLR 231:26:1-26:18

[abs][Download PDF][OpenReview][Software][Supplementary ZIP]

KGEx: Explaining Knowledge Graph Embeddings via Subgraph Sampling and Knowledge Distillation

Vasileios Baltatzis, Luca Costabello; Proceedings of the Second Learning on Graphs Conference, PMLR 231:27:1-27:13

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Neural Algorithmic Reasoning for Combinatorial Optimisation

Dobrik Georgiev Georgiev, Danilo Numeroso, Davide Bacciu, Pietro Lio; Proceedings of the Second Learning on Graphs Conference, PMLR 231:28:1-28:15

[abs][Download PDF][OpenReview][Software][Supplementary ZIP]

A Latent Diffusion Model for Protein Structure Generation

Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael Curtis McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji; Proceedings of the Second Learning on Graphs Conference, PMLR 231:29:1-29:17

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United We Stand, Divided We Fall: Networks to Graph (N2G) Abstraction for Robust Graph Classification Under Graph Label Corruption

Zhiwei Zhen, Yuzhou Chen, Murat Kantarcioglu, Kangkook Jee, Yulia Gel; Proceedings of the Second Learning on Graphs Conference, PMLR 231:30:1-30:19

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Parallel Algorithms Align With Neural Execution

Valerie Engelmayer, Dobrik Georgiev Georgiev, Petar Veličković; Proceedings of the Second Learning on Graphs Conference, PMLR 231:31:1-31:13

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Generative Modeling of Labeled Graphs Under Data Scarcity

Sahil Manchanda, Shubham Gupta, Sayan Ranu, Srikanta J. Bedathur; Proceedings of the Second Learning on Graphs Conference, PMLR 231:32:1-32:18

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MUDiff: Unified Diffusion for Complete Molecule Generation

Chenqing Hua, Sitao Luan, Minkai Xu, Zhitao Ying, Jie Fu, Stefano Ermon, Doina Precup; Proceedings of the Second Learning on Graphs Conference, PMLR 231:33:1-33:26

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HEAL: Unlocking the Potential of Learning on Hypergraphs Enriched With Attributes and Layers

Naganand Yadati, Tarun Kumar, Deepak Maurya, Balaraman Ravindran, Partha Talukdar; Proceedings of the Second Learning on Graphs Conference, PMLR 231:34:1-34:25

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Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks

Andreas Roth, Thomas Liebig; Proceedings of the Second Learning on Graphs Conference, PMLR 231:35:1-35:23

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Semi-Supervised Learning for High-Fidelity Fluid Flow Reconstruction

Cong Fu, Jacob Helwig, Shuiwang Ji; Proceedings of the Second Learning on Graphs Conference, PMLR 231:36:1-36:19

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BeMap: Balanced Message Passing for Fair Graph Neural Network

Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong; Proceedings of the Second Learning on Graphs Conference, PMLR 231:37:1-37:25

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Rethinking Higher-Order Representation Learning With Graph Neural Networks

Tuo Xu, Lei Zou; Proceedings of the Second Learning on Graphs Conference, PMLR 231:38:1-38:25

[abs][Download PDF][OpenReview][Supplementary ZIP]