Abstract is missing.
- The Second Learning on Graphs Conference: PrefaceSoledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson 0001, Yanqiao Zhu 0001, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan. [doi]
- Representing Edge Flows on Graphs via Sparse Cell ComplexesJosef Hoppe, Michael T. Schaub. 1 [doi]
- Meta-Path Learning for Multi-Relational Graph Neural NetworksFrancesco Ferrini, Antonio Longa, Andrea Passerini, Manfred Jaeger. 2 [doi]
- Asynchronous Algorithmic Alignment With CocyclesAndrew Joseph Dudzik, Tamara von Glehn, Razvan Pascanu, Petar Velickovic. 3 [doi]
- Cycle Invariant Positional Encoding for Graph Representation LearningZuoYu Yan, Tengfei Ma 0001, Liangcai Gao, Zhi Tang 0001, Chao Chen 0012, Yusu Wang 0001. 4 [doi]
- Recursive Algorithmic ReasoningJonas Jürß, Dulhan Hansaja Jayalath, Petar Velickovic. 5 [doi]
- On Performance Discrepancies Across Local Homophily Levels in Graph Neural NetworksDonald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra. 6 [doi]
- Spectral Subgraph LocalizationAma Bembua Bainson, Judith Hermanns, Petros Petsinis, Niklas Aavad, Casper Dam Larsen, Tiarnan Swayne, Amit Boyarski, Davide Mottin, Alex M. Bronstein, Panagiotis Karras. 7 [doi]
- GwAC: GNNs With Asynchronous CommunicationLukas Faber, Roger Wattenhofer. 8 [doi]
- GSCAN: Graph Stability Clustering for Applications With Noise Using Edge-Aware Excess-of-MassEtzion Harari, Naphtali Abudarham, Roee Litman. 9 [doi]
- Latent Space Representations of Neural Algorithmic ReasonersVladimir V. Mirjanic, Razvan Pascanu, Petar Velickovic. 10 [doi]
- Multicoated and Folded Graph Neural Networks With Strong Lottery TicketsJiale Yan, Hiroaki Ito, Ángel López García-Arias, Yasuyuki Okoshi, Hikari Otsuka, Kazushi Kawamura, Thiem Van Chu, Masato Motomura. 11 [doi]
- PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed GraphsYixuan He, Xitong Zhang, Junjie Huang, Benedek Rozemberczki, Mihai Cucuringu, Gesine Reinert. 12 [doi]
- SURF: A Generalization Benchmark for GNNs Predicting Fluid DynamicsStefan Künzli, Florian Grötschla, Joël Mathys, Roger Wattenhofer. 13 [doi]
- Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural NetworksJing Gu, Dongmian Zou. 14 [doi]
- HOT: Higher-Order Dynamic Graph Representation Learning With Efficient TransformersMaciej Besta, Afonso Claudino Catarino, Lukas Gianinazzi, Nils Blach, Piotr Nyczyk, Hubert Niewiadomski, Torsten Hoefler. 15 [doi]
- Generalized Reasoning With Graph Neural Networks by Relational Bayesian Network EncodingsRaffaele Pojer, Andrea Passerini, Manfred Jaeger. 16 [doi]
- Non-Isotropic Persistent Homology: Leveraging the Metric Dependency of PHVincent Peter Grande, Michael T. Schaub. 17 [doi]
- Transferable Hypergraph Neural Networks via Spectral SimilarityMikhail Hayhoe, Hans Riess, Michael M. Zavlanos, Victor M. Preciado, Alejandro Ribeiro. 18 [doi]
- Mitigating Over-Smoothing and Over-Squashing Using Augmentations of Forman-Ricci CurvatureLukas Fesser, Melanie Weber 0001. 19 [doi]
- Interaction Models and Generalized Score Matching for Compositional DataShiqing Yu, Mathias Drton, Ali Shojaie. 20 [doi]
- Will More Expressive Graph Neural Networks Do Better on Generative Tasks?Xiandong Zou, Xiangyu Zhao, Pietro Lio, Yiren Zhao. 21 [doi]
- Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With PerturbationsDhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy. 22 [doi]
- Intrinsically Motivated Graph Exploration Using Network Theories of Human CuriosityShubhankar Prashant Patankar, Mathieu Ouellet, Juan Cerviño, Alejandro Ribeiro, Kieran A. Murphy, Danielle S. Bassett. 23 [doi]
- EMP: Effective Multidimensional Persistence for Graph Representation LearningYuzhou Chen, Ignacio Segovia-Dominguez, Cuneyt Gurcan Akcora, Zhiwei Zhen, Murat Kantarcioglu, Yulia R. Gel, Baris Coskunuzer. 24 [doi]
- Edge Directionality Improves Learning on Heterophilic GraphsEmanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein. 25 [doi]
- A Simple Latent Variable Model for Graph Learning and InferenceManfred Jaeger, Antonio Longa, Steve Azzolin, Oliver Schulte, Andrea Passerini. 26 [doi]
- KGEx: Explaining Knowledge Graph Embeddings via Subgraph Sampling and Knowledge DistillationVasileios Baltatzis, Luca Costabello. 27 [doi]
- Neural Algorithmic Reasoning for Combinatorial OptimisationDobrik Georgiev, Danilo Numeroso, Davide Bacciu, Pietro Lio. 28 [doi]
- A Latent Diffusion Model for Protein Structure GenerationCong Fu 0003, Keqiang Yan, Limei Wang, Wing Yee Au, Michael McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji. 29 [doi]
- United We Stand, Divided We Fall: Networks to Graph (N2G) Abstraction for Robust Graph Classification Under Graph Label CorruptionZhiwei Zhen, Yuzhou Chen, Murat Kantarcioglu, Kangkook Jee, Yulia R. Gel. 30 [doi]
- Parallel Algorithms Align With Neural ExecutionValerie Engelmayer, Dobrik Georgiev, Petar Velickovic. 31 [doi]
- Generative Modeling of Labeled Graphs Under Data ScarcitySahil Manchanda, Shubham Gupta, Sayan Ranu, Srikanta J. Bedathur. 32 [doi]
- MUDiff: Unified Diffusion for Complete Molecule GenerationChenqing Hua, Sitao Luan, Minkai Xu, Zhitao Ying, Jie Fu, Stefano Ermon, Doina Precup. 33 [doi]
- HEAL: Unlocking the Potential of Learning on Hypergraphs Enriched With Attributes and LayersNaganand Yadati, Tarun Kumar, Deepak Maurya, Balaraman Ravindran, Partha P. Talukdar. 34 [doi]
- Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural NetworksAndreas Roth, Thomas Liebig. 35 [doi]
- Semi-Supervised Learning for High-Fidelity Fluid Flow ReconstructionCong Fu 0003, Jacob Helwig, Shuiwang Ji. 36 [doi]
- BeMap: Balanced Message Passing for Fair Graph Neural NetworkXiao Lin, Jian Kang, Weilin Cong, Hanghang Tong. 37 [doi]
- Rethinking Higher-Order Representation Learning With Graph Neural NetworksTuo Xu, Lei Zou. 38 [doi]