Graph Neural Networks

Follow this field Ask about this field

Recent momentum

emerging

0 papers in the last 28 days · 0.0% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Weekly history

Recent digests

What was published in this field, kept on the site without email delivery.

Period ending 2026-09-21

38 new papers

A weekly snapshot of new work published in Graph Neural Networks.

Period ending 2026-09-14

19 new papers

A weekly snapshot of new work published in Graph Neural Networks.

Period ending 2026-09-07

22 new papers

A weekly snapshot of new work published in Graph Neural Networks.

Inside this field

Focused directions

Focused topic

Graph Neural Networks

Within Graph Neural Networks

422 papersExplore

Focused topic

Graph Representations

Within Graph Neural Networks

201 papersExplore

Focused topic

Graph Representation Learning

Within Graph Neural Networks

192 papersExplore

Focused topic

Heterogeneous Graph Transformers

Within Graph Neural Networks

69 papersExplore

Focused topic

Graph Foundation Model

Within Graph Neural Networks

58 papersExplore

Focused topic

Maximum Independent Set

Within Graph Neural Networks

56 papersExplore

Focused topic

Text-Attributed Graph

Within Graph Neural Networks

50 papersExplore

Focused topic

Message Passing Neural Networks

Within Graph Neural Networks

48 papersExplore

Focused topic

Subgraphs

Within Graph Neural Networks

44 papersExplore

Focused topic

Gnn-Based Detectors

Within Graph Neural Networks

42 papersExplore

Focused topic

Graph Theory

Within Graph Neural Networks

42 papersExplore

Focused topic

Exponential Random Graph Models

Within Graph Neural Networks

28 papersExplore

1,049 papers

Latest in Graph Neural Networks

Browse all topics →

Spectral bandits for smooth graph functions with applications in recommender systems
May 19, 2026Tomáš Kocák, Michal Valko, Rémi Munos +2Large-Scale Recommendation Systems Recommender Systems
Contradiction Graphs Determine VC Dimension
May 19, 2026Jesse Campbell, Daniel Ibaibarriaga, Lev ReyzinGraph Theory Product Spaces
Towards Distillation Guarantees under Algorithmic Alignment for Combinatorial Optimization
May 19, 2026Thien Le, Melanie WeberProgressive Distillation Combinatorial Optimization
Exploiting Non-Negativity in DAG Structure Learning
May 19, 2026Samuel Rey, Madeline navarro, Gonzalo MateosGraph Representation Learning Lagrangian Methods
Fast and Featureless Node Representation Learning with Partial Pairwise Supervision
May 19, 2026Sujan Chakraborty, Saptarshi BejGraph Representation Learning Graph Neural Networks
Hierarchical Contrastive Learning for Multi-Domain Protein-Ligand Binding
May 19, 2026Shuo Zhang, Rongqi Hong, Huifeng Zhang +1Structure-Based Drug Design Multi-Domain
B-cos GNNs: Faithful Explanations through Dynamic Linearity
May 19, 2026Joschka Groß, Mohammad Shaique Solanki, Verena WolfExplainability Graph Neural Networks
Graph Neural Networks for Community Detection in Graph Signal Analysis
May 19, 2026Roberto Cavoretto, Alessandra De Rossi, Enrico MontiniGraph Neural Networks Interpolation
Projecting Latent RL Actions: Towards Generalizable and Scalable Graph Combinatorial Optimization
May 19, 2026Franco Terranova, Guillermo Bernardez, Albert Cabellos-Aparicio +2Combinatorial Optimization Graph Representations
Physics-Informed Graph Neural Network Surrogates for Turbulent Nanoparticle Dispersion in Dental Clinical Environments
May 19, 2026Takshak Shende, Viktor PopovComputational Fluid Dynamic Lagrangian Methods
A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning
May 19, 2026Honglin Du, Muxuan Liang, Xiang ZhongCausal Graph Directed Acyclic Graph
Do Better Volatility Forecasts Lead to Better Portfolios? Evidence from Graph Neural Networks
May 19, 2026Rylan WadeStochastic Volatility Portfolio Optimization
Euclidean Embedding of Data Using Local Distances
May 19, 2026Dimitris ArabadjisManifold Learning Method Distance
Planner-Admissible Graph-PDE Value Extensions for Sparse Goal-Conditioned Planning
May 18, 2026Shiheng ZhangClassical Planning Planning Methods
Deep Neural Sheaf Diffusion
May 18, 2026Rémi Bourgerie, Šarūnas Girdzijauskas, Viktoria FodorGraph Neural Networks Sheaf
S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs
May 18, 2026Yuhan Wang, Haopeng Zhang, Yibo Ding +6Text-Attributed Graph Large Language Model Alignment
Graph Hierarchical Recurrence for Long-Range Generalization
May 18, 2026Stefano Carotti, Marco Pacini, Alessio Gravina +3Graph Neural Networks Long-Range Temporal Dependencies
Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors
May 18, 2026Aldric LabartheBayesian Exponential Random Graph Models
Leveraging Graph Structure in Seq2Seq Models for Knowledge Graph Link Prediction
May 18, 2026Luu Huu Phuc, Ratan Bahadur Thapa, Mojtaba Nayyeri +3Zero-Shot Link Prediction Knowledge Graph Embeddings
POST: Prior-Observation Adversarial Learning of Spatio-Temporal Associations for Multivariate Time Series Anomaly Detection
May 18, 2026Suofei Zhang, Yaxuan Zheng, Haifeng HuTime-Series Anomaly Detection Anomaly Detection
Topological Signal Processing: An Application-Oriented Tutorial
May 18, 2026Flavia Petruso, Maria Giulia Preti, Dimitri Van De VilleSignal Processing Graph Representations
Functionalization via Structure Completion and Motion Rectification
May 18, 2026Mingrui Zhao, Sai Raj Kishore Perla, Kai Wang +83D Models 3D Object Understanding
Function graph transformers universally approximate operators between function spaces
May 18, 2026Takashi Furuya, David Mis, Ivan Dokmanić +2Probabilistic Operator Learning Heterogeneous Graph Transformers
Expressive Power of Deep Homomorphism Networks over Relational Databases
May 18, 2026Moritz Schönherr, Balder ten Cate, Maurice Funk +3Relational Deep Learning Graph Neural Networks
Learning over Positive and Negative Edges with Contrastive Message Passing
May 18, 2026Peter Pao-Huang, Charilaos I. Kanatsoulis, Michael Bereket +1Message Passing Neural Networks Graph Representations
SCAFDS: Edge-Feature Graph Attention for Interbank Fraud Detection with Attribution-Grounded SAR Generation
May 17, 2026Mohammad Nasir UddinFraud Detection Heterogeneous Graph Transformers
TriOpt: A Scalable Algorithm for Linear Causal Discovery
May 17, 2026Rafat Ashraf Joy, Elena ZhelevaCausal Foundation Models Causal Reasoning
Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning
May 17, 2026Wei Duan, Junyu Xuan, En Yu +2Multi-Agent Reinforcement Learning Coordination
Bridging the Gap between Sparse Matrix Reordering and Factorization: A Deep Learning Framework for Fill-in Reduction
May 17, 2026Ziwei Li, Tao Yuan, Shuzi Niu +1Matrix Factorization Factor
Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence
May 17, 2026Mridul Gupta, Samyak Jain, Vansh Ramani +2Graph Neural Networks Position
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
May 17, 2026Hyunju Kang, Geonhee Han, Hogun ParkCounterfactual Explanation Graph Representation Learning
CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials
May 17, 2026Yanjie Li, Jian Xu, Xu-Yao Zhang +4Heterogeneous Catalysis Generative Inverse Design
Filter-then-Verify: A Multiphase GNN and ModernBERT Framework for Social Engineering Detection in Email Networks
May 17, 2026Barsat Khadka, Prasant Koirala, Kshitiz Neupane +1Phishing Attack Detection
ArtifactLinker: Linking Scientific Artifacts for Automatic State-of-the-Art Discovery
May 16, 2026Haofei Yu, Jiaxuan You, Peter Clark +2State-Of-The-Art Graph Neural Networks
Tensor Channel Equivariant Graph Neural Networks for Molecular Polarizability Prediction
May 16, 2026Jean Philip Filling, Daniel Franzen, Michael WandMolecular Property Prediction Tensor Networks
Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities
May 16, 2026Sha Tao, Jiao Pan, Yu Guo +1Brain Tumor Segmentation Missing Modalities
Universal Graph Backdoor Defense: A Feature-based Homophily Perspective
May 16, 2026Mengting Pan, Fan Li, Chen Chen +1Backdoor Attacks Graph Neural Networks
Informative Graph Structure Learning
May 16, 2026Shen Han, Zhiyao Zhou, Jiawei Chen +6Graph Representation Learning Mutual Information
A Global-Local Graph Attention Network for Traffic Forecasting
May 16, 2026Tianchi ZhangAccurate Traffic Forecasting Temporal Graph Neural Networks
GRID: Graph Representation of Intelligence Data for Security Text Knowledge Graph Construction
May 15, 2026Liangyi Huang, Zichen Liu, Fei Shao +5Knowledge Graphs Graph Representations
Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks
May 15, 2026Jingcheng Wu, Ratan Bahadur Thapa, Mojtaba Nayyeri +4Relational Deep Learning Relational
CHoE: Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned Experts
May 15, 2026Peiyuan Li, Yongqi Huang, Jitao Zhao +3Graph Foundation Model Mixture-of-Experts Models
GOMA: Toward Structure-Driven Multimodal Alignment from a Graph Signal Smoothing Perspective
May 15, 2026Xu Wang, Xunkai Li, Yinlin Zhu +2Multimodal Alignment Modality-Specific Encoders
SEED: Targeted Data Selection by Weighted Independent Set
May 15, 2026Yuan Zhang, Lifeng Guo, Junwen Pan +5Geometry-Aware Uncertainty Coresets Heterogeneity
Physics-Guided Geometric Diffusion for Macro Placement Generation
May 15, 2026Jongho Yoon, Jinsung Jeon, Seokhyeong KangLayouts Chip Design
Gaussian Relational Graph Transformer
May 15, 2026Zezhong Ding, Jin Li, Xugang Wang +1Heterogeneous Graph Transformers Spatio-Temporal Transformers
OgBench: A Framework for Evaluating Graph Neural Networks on Omics Data
May 15, 2026Louisa Cornelis, Johan Mathe, Louis Van Langendonck +2Multi-Omic Framework Graph Neural Networks
A Unified Non-Parametric and Interpretable Point Cloud Analysis via t-FCW Graph Representation
May 14, 2026Haijian Lai, Bowen Liu, Man Xu +4Graph Representation Learning Graph Representations
Njord: A Probabilistic Graph Neural Network for Ensemble Ocean Forecasting
May 14, 2026Daniel Holmberg, Joel Oskarsson, Erik Wikingsson +2Shallow Water Equations Neural Network
Controllable Molecular Generative Foundation Models
May 14, 2026Yihan Zhu, Yuhan Liu, Weijiang Li +2Molecular Generation Generative Models
GraphFlow: An Architecture for Formally Verifiable Visual Workflows Enabling Reliable Agentic AI Automation
May 14, 2026Drewry H. Morris, Luis Valles, Reza Hosseini GhomiAgentic Workflows Workflow Automation and Optimization
AIMing for Standardised Explainability Evaluation in GNNs: A Framework and Case Study on Graph Kernel Networks
May 14, 2026Magdalena Proszewska, N. SiddharthExplainability Graph Neural Networks
Exploitation of Hidden Context in Dynamic Movement Forecasting: A Neural Network Journey from Recurrent to Graph Neural Networks and General Purpose Transformers
May 14, 2026Lukas Schelenz, Shobha Rajanna, Denis Gosalci +6Trajectory Prediction Temporal Convolutional Networks
GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning
May 14, 2026Yan Jiang, Ruihong Qiu, Zi HuangGraph Foundation Model
Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity
May 14, 2026Abolfazl Zarghani, Amir MalekesfandiariNeuro-Symbolic Framework Gnn-Based Detectors
Nearest-Neighbor Radii under Dependent Sampling
May 14, 2026Yuanyuan Gao, Yilong Hou, Zhexiao LinApproximate Nearest-Neighbor Search Intrinsic Dimensionality
Why Retrieval-Augmented Generation Fails: A Graph Perspective
May 13, 2026Kai Guo, Xinnan Dai, Zhibo Zhang +5Multi-Hop Question Answering Benchmarks Graph Representations
Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation
May 13, 2026Haoran Li, Tobias Lehrer, Yingxue Zhao +5Graph Neural Networks Surrogate Models
Graph Neural Networks with Triangle-Based Messages for the Multicut Problem
May 13, 2026Jannik Irmai, Lucas Fabian Naumann, Bjoern AndresMaximum Independent Set Graph Neural Networks
Rethinking Graph Convolution for 2D-to-3D Hand Pose Lifting
May 13, 2026Chanyoung Kim, Donghyun Kim, Dong-Hyun Sim +23D Hand Heterogeneous Graph Transformers

May 19, 2026 · stat.MLJ/K move · Enter open · S save

Spectral bandits for smooth graph functions with applications in recommender systems

Tomáš Kocák, Michal Valko, Rémi Munos, Branislav Kveton+1

SequeL team Inria Lille France · SequeL team, Inria France · Microsoft Research New England · Technicolor Research Center California · Microsoft Research Bangalore India

Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this paper, we study a bandit problem where the payoffs of arms are smooth on a graph. This framework is suitable for solving online learning problems that involve graphs, such as content-based recommendation. In this problem, each recommended item is a node and its expected rating is similar to its neighbors. The goal is to recommend items that have high expected ratings. We aim for the algorithms where the cumulative regret would not scale poorly with the number of nodes. In particular, we introduce the notion of an effective dimension, which is small in real-world graphs, and propose two algorithms for solving our problem that scale linearly in this dimension. Our experiments on real-world content recommendation problem show that a good estimator of user preferences for thousands of items can be learned from just tens nodes evaluations.

Large-Scale Recommendation Systems Recommender Systems Multi-Armed Bandits Bandits Graph Representation Learning Smoothing Semi-Supervised Learning

Open paper Ask about it PDF