[ICLR'24] Learning on Graphs

Title	Authors	OpenReview
DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption	Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo	here
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks	Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo	here
PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation	Haopeng Sun, Lumin Xu, Sheng Jin, Ping Luo, Chen Qian, Wentao Liu	here
Graphpulse: Topological representations for temporal graph property prediction	Kiarash Shamsi, Farimah Poursafaei, Shenyang(Andy) Huang, Tran Gia Bao Ngo, Baris Coskunuzer, Cuneyt Akcora	here
GnnX-Bench: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking	Mert Kosan, Samidha Verma, Burouj Armgaan, Khushbu Pahwa, Ambuj K Singh, Sourav Medya, Sayan Ranu	here
GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs	Pengcheng Jiang, Cao Xiao, Adam Cross, Jimeng Sun	here
Improving Generalization in Equivariant Graph Neural Networks with Physical Inductive Biases	Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong	here
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs	Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, RISHITA ANUBHAI	here
Scalable and Effective Implicit Graph Neural Networks on Large Graphs	Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao	here
A Differentially Private Clustering Algorithm for Well-Clustered Graphs	Weiqiang He, Hendrik Fichtenberger, Pan Peng	here
Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs	Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Manish Singh, Toyotaro Suzumura	here
Contrastive Learning is Spectral Clustering on Similarity Graph	Yifan Zhang, Zhiquan Tan, Jingqin Yang, Yang Yuan	here
Talk like a Graph: Encoding Graphs for Large Language Models	Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi	here
Uncertainty-aware Graph-based Hyperspectral Image Classification	Linlin Yu, Yifei Lou, Feng Chen	here
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks	Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z Li	here
On the Stability of Expressive Positional Encodings for Graph Neural Networks	Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li	here
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning	Adyasha Maharana, Prateek Yadav, Mohit Bansal	here
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks	Wenxi Wang, Yang Hu, Mohit Tiwari, Sarfraz Khurshid, Kenneth McMillan, Risto Miikkulainen	here
Neural Common Neighbor with Completion for Link Prediction	Xiyuan Wang, Haotong Yang, Muhan Zhang	here
From Graphs to Hypergraphs: Hypergraph Projection and its Remediation	Yanbang Wang, Jon Kleinberg	here
Counting Graph Substructures with Graph Neural Networks	Charilaos Kanatsoulis, Alejandro Ribeiro	here
Adversarial Attacks on Fairness of Graph Neural Networks	Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li	here
Graph Transformers on EHRs: Better Representation Improves Downstream Performance	Raphael Poulain, Rahmatollah Beheshti	here
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning	Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montaña-Brown, Tiantian He, Ayodeji Ijishakin, Ivana Drobnjak, Daniel Castro, Daniel Alexander	here
GRAPH-CONSTRAINED DIFFUSION FOR END-TO-END PATH PLANNING	DINGYUAN SHI, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye	here
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs	Florian Grötschla, Joël Mathys, Róbert Veres, Roger Wattenhofer	here
Universal Graph Random Features	Isaac Reid, Krzysztof Choromanski, Eli Berger, Adrian Weller	here
A Simple and Scalable Representation for Graph Generation	Yunhui Jang, Seul Lee, Sungsoo Ahn	here
Towards Foundation Models for Knowledge Graph Reasoning	Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu	here
Training Graph Transformers via Curriculum-Enhanced Attention Distillation	Yisong Huang, Jin Li, Xinlong Chen, Yang-Geng Fu	here
Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors	Hang Yin, Zihao Wang, Yangqiu Song	here
Graph Metanetworks for Processing Diverse Neural Architectures	Derek Lim, Haggai Maron, Marc T Law, Jonathan Lorraine, James Lucas	here
Deceptive Fairness Attacks on Graphs via Meta Learning	Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong	here
Graph Parsing Networks	Yunchong Song, Siyuan Huang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin	here
Conformal Inductive Graph Neural Networks	Soroush H. Zargarbashi, Aleksandar Bojchevski	here
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time	Chenhui Deng, Zichao Yue, Zhiru Zhang	here
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks	Federico Errica, Mathias Niepert	here
Efficient Subgraph GNNs by Learning Effective Selection Policies	Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron	here
DyVal: Graph-informed Dynamic Evaluation of Large Language Models	Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Gong, Diyi Yang, Xing Xie	here
PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks	Junwei Su, Difan Zou, Chuan Wu	here
One For All: Towards Training One Graph Model For All Classification Tasks	Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang	here
GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries	Xiaoqi Wang, Han Wei Shen	here
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries	Haitz Sáez de Ocáriz Borde, Anastasis Kratsios	here
iGraphMix: Input Graph Mixup Method for Node Classification	Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon, Beomyoung Lee, Junhee Heo, Geonsoo Kim, Kim Jin Seon	here
A Stochastic Centering Framework for Improving Calibration in Graph Neural Networks	Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan	here
Deep Temporal Graph Clustering	Meng Liu, Yue Liu, KE LIANG, Wenxuan Tu, Siwei Wang, sihang zhou, Xinwang Liu	here
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach	Aoqi Zuo, yiqing li, Susan Wei, Mingming Gong	here
A Generative Pre-Training Framework for Spatio-Temporal Graph Transfer Learning	Yuan Yuan, Chenyang Shao, Jingtao Ding, Depeng Jin, Yong Li	here
Learning Multi-Agent Communication from Graph Modeling Perspective	Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao	here
Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs	Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han	here
From Matching to Mixing: A Graph Interpolation Approach for SAT Instance Generation	Xinyan Chen, Yang Li, Runzhong Wang, Junchi Yan	here
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module	Claudio Battiloro, Indro Spinelli, Lev Telyatinkov, Michael Bronstein, Simone Scardapane, Paolo Di Lorenzo	here
Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values.	Xiaodan Chen, Xiucheng Li, Bo Liu, Zhijun Li	here
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior	Chenguo Lin, Yadong MU	here
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks	Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen	here
HiGen: Hierarchical Graph Generative Networks	Mahdi Karami	here
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-Image Generation	Jaemin Cho, Yushi Hu, Jason Baldridge, Roopal Garg, Peter Anderson, Ranjay Krishna, Mohit Bansal, Jordi Pont-Tuset, Su Wang	here
GraphGuard: Provably Robust Graph Classification against Adversarial Attacks	Zaishuo Xia, Han Yang, Binghui Wang, Jinyuan Jia	here
Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness	Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang	here
HoloNets: Spectral Convolutions do extend to Directed Graphs	Christian Koke, Daniel Cremers	here
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks	Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski	here
Long-range Neural Atom Learning for Molecular Graphs	Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han	here
Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations	Giovanni De Felice, Andrea Cini, Daniele Zambon, Vladimir Gusev, Cesare Alippi	here
Complete and Efficient Graph Transformers for Crystal Material Property Prediction	Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji	here
Forward Learning of Graph Neural Networks	Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan Rossi, Puja Trivedi, Nesreen Ahmed	here
Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks	Kesen Zhao, Liang Zhang	here
Local Graph Clustering with Noisy Labels	Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang	here
Rethinking and Extending the Probabilistic Inference Capacity of GNNs	Tuo Xu, Lei Zou	here
Robust Angular Synchronization via Directed Graph Neural Networks	Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu	here
TEDDY: Trimming Edges with Degree-based Graph Diffusion Strategy	Hyunjin Seo, Jihun Yun, Eunho Yang	here
Locality-Aware Graph Rewiring in GNNs	Federico Barbero, Ameya Velingker, Amin Saberi, Michael Bronstein, Francesco Di Giovanni	here
Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection	Xiangyu Dong, Xingyi Zhang, Sibo WANG	here
BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics	Suresh Bishnoi, Jayadeva Jayadeva, Sayan Ranu, N. M. Anoop Krishnan	here
Efficient and Scalable Graph Generation through Iterative Local Expansion	Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer	here
GOAt: Explaining Graph Neural Networks via Graph Output Attribution	Shengyao Lu, Keith G Mills, Jiao He, Bang Liu, Di Niu	here
Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials	Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram Deshpande	here
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs	Thien Le, Luana Ruiz, Stefanie Jegelka	here
Transformers vs. Message Passing GNNs: Distinguished in Uniform	Jan Tönshoff, Eran Rosenbluth, Martin Ritzert, Berke Kisin, Martin Grohe	here
Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision	Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen	here
LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference	Yifan Feng, Yihe Luo, Shihui Ying, Yue Gao	here
Hypergraph Dynamic System	Jielong Yan, Yifan Feng, Shihui Ying, Yue Gao	here
Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View	YUJIE MO, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu	here
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs	Milan Papez, Martin Rektoris, Tomáš Pevný, Vaclav Smidl	here
Label-free Node Classification on Graphs with Large Language Models (LLMs)	Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang	here
Mayfly: a Neural Data Structure for Graph Stream Summarization	yuan feng, Yukun Cao, Hairu Wang, Xike Xie, S Kevin Zhou	here
GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks	Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer	here
Adaptive Self-training Framework for Fine-grained Scene Graph Generation	Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park	here
Structural Fairness-aware Active Learning for Graph Neural Networks	Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada	here
Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network	Tianze Luo, Zhanfeng Mo, Sinno Pan	here
VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition	Chenyu Liu, XINLIANG ZHOU, Zhengri Zhu, Liming Zhai, Ziyu Jia, Yang Liu	here
Online GNN Evaluation Under Test-time Graph Distribution Shifts	Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan	here
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability	Zehao Dong, Muhan Zhang, Philip Payne, Michael Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen	here
Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach	Christian Fabian, Kai Cui, Heinz Koeppl	here
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs	Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin CUI, Muhan Zhang, Jure Leskovec	here
Latent 3D Graph Diffusion	Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen	here
Graph Neural Networks for Learning Equivariant Representations of Neural Networks	Miltiadis (Miltos) Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J Burghouts, Efstratios Gavves, Cees G Snoek, David Zhang	here
Graph Generation with $K^2$-trees	Yunhui Jang, Dongwoo Kim, Sungsoo Ahn	here
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering	Jiaxin Lu, Zetian Jiang, Tianzhe Wang, Junchi Yan	here
NP-GL: Extending Power of Nature from Binary Problems to Real-World Graph Learning	Chunshu Wu, Ruibing Song, Chuan Liu, Yunan Yang, Ang Li, Michael Huang, Tong Geng	here
Clifford Group Equivariant Simplicial Message Passing Networks	Cong Liu, David Ruhe, Floor Eijkelboom, Patrick Forré	here
FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction	Yuxing Tian, Yiyan Qi, Fan Guo	here
MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy	Yan Sun, Jicong Fan	here
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning	Linhao Luo, Yuan-Fang Li, Reza Haffari, Shirui Pan	here
Revisiting Link Prediction: a data perspective	Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang	here
Mixture of Weak and Strong Experts on Graphs	Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo	here
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections	Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long	here
Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks	Yassine ABBAHADDOU, Sofiane ENNADIR, Johannes Lutzeyer, Michalis Vazirgiannis, Henrik Boström	here
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning	Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi	here
Mitigating Severe Robustness Degradation on Graphs	Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang	here
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph	Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Saizhuo Wang, Chen Lin, Yeyun Gong, Lionel Ni, Heung-Yeung Shum, Jian Guo	here
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models	Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang	here
Orbit-Equivariant Graph Neural Networks	Matthew Morris, Bernardo Grau, Ian Horrocks	here
Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning	Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie, Vaibhav Rajan	here
Boosting Graph Anomaly Detection with Adaptive Message Passing	Jingyan Chen, Guanghui Zhu, Chunfeng Yuan, Yihua Huang	here
Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND	Qiyu Kang, Kai Zhao, Qinxu Ding, Feng Ji, Xuhao Li, Wenfei Liang, Yang Song, Wee Peng Tay	here
Temporal Generalization Estimation in Evolving Graphs	Bin Lu, Tingyan Ma, Xiaoying Gan, Xinbing Wang, Yunqiang Zhu, Chenghu Zhou, Shiyu Liang	here
Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks	Shih-Hsin Wang, Yung-Chang Hsu, Justin Baker, Andrea Bertozzi, Jack Xin, Bao Wang	here
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes	Jiawei Sun, Kailai Li, Ruoxin Chen, Jie LI, Chentao Wu, Yue Ding, Junchi Yan	here
Graph Lottery Ticket Automated	Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng, Yuxuan Liang	here
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning	Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi	here
Partitioning Message Passing for Graph Fraud Detection	Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen	here
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data	Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji	here
On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters	Matthias Lanzinger, Pablo Barcelo	here
Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective	Kuan Li, YiWen Chen, Yang Liu, Jin Wang, QING HE, Minhao Cheng, Xiang Ao	here
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance	Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr	here
Hybrid Directional Graph Neural Network for Molecules	Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Xu Yinghui, Yuan Qi, Furao Shen	here
Mirage: Model-agnostic Graph Distillation for Graph Classification	Mridul Gupta, Sahil Manchanda, HARIPRASAD KODAMANA, Sayan Ranu	here
PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters	Jingyu Chen, Runlin Lei, Zhewei Wei	here
StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning	Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, Zengfeng Huang	here
GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation	Guikun Xu, Yongquan Jiang, PengChuan Lei, Yan Yang, Jim Chen	here