Deep learning · graph neural networks papers, 2023–2026

Key findings

• Deep learning · graph neural networks fell from 728 papers in 2023 to 326 in 2026, so interest is cooling.
• NeurIPS publishes the most Deep learning · graph neural networks work: 842 papers from 2023 to 2026, 51% of the four-venue total.
• The fastest-growing overlap is with Datasets and Benchmarks: papers tagged with both rose from 9 in 2023 to 20 in 2026.
• Among the 11 topics under Deep Learning, it ranks #5 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 0.4x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A New Perspective on Target-Conditioned Structural Dynamics for Link Prediction in Dynamic Graphs
• ICML 2026A Graph Foundation Model with Cross-Modal Alignment and Modality-Aware Expert Fusion for Multi-Modal Graphs
• ICLR 2026Laplacian Kernelized Bandit
• CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
• NeurIPS 2025Depth-Width Tradeoffs for Transformers on Graph Tasks
• ICML 2025A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
• ICLR 2025Factor Graph-based Interpretable Neural Networks
• CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
• NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
• ICML 2024A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Learning Structure-from-Motion with Graph Attention Networks
• NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
• ICML 2023A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
• ICLR 2023Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
• CVPR 2023An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity
• NeurIPS 2026A Topological Encoder Decoder Framework for Temporal Graph Learning
• ICML 2026A Graphop Analysis of Graph Neural Networks on Sparse Graphs: Generalization and Universal Approximation
• ICLR 2026GTool: Graph Enhanced Tool Planning with Large Language Model
• CVPR 2026GSNR Graph Smooth Null-Space Representation for Inverse Problems

All Deep learning · graph neural networks papers

1,648 papers, page 20 of 33

951. ICLR 2023Are More Layers Beneficial to Graph Transformers?
952. ICLR 2023AutoGT: Automated Graph Transformer Architecture Search
953. ICLR 2023Automated Data Augmentations for Graph Classification
954. ICLR 2023AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks
955. ICLR 2023Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs
956. ICLR 2023Characterizing the Influence of Graph Elements
957. ICLR 2023Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation
958. ICLR 2023DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
959. ICLR 2023DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
960. ICLR 2023Do We Really Need Complicated Model Architectures For Temporal Networks?
961. ICLR 2023Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
962. ICLR 2023Effects of Graph Convolutions in Multi-layer Networks
963. ICLR 2023Efficient Model Updates for Approximate Unlearning of Graph-Structured Data
964. ICLR 2023Energy-based Out-of-Distribution Detection for Graph Neural Networks
965. ICLR 2023Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
966. ICLR 2023ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
967. ICLR 2023Fair Attribute Completion on Graph with Missing Attributes
968. ICLR 2023FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
969. ICLR 2023Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation
970. ICLR 2023Graph Contrastive Learning for Skeleton-based Action Recognition
971. ICLR 2023Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
972. ICLR 2023Graph Neural Networks for Link Prediction with Subgraph Sketching
973. ICLR 2023Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution
974. ICLR 2023GReTo: Remedying dynamic graph topology-task discordance via target homophily
975. ICLR 2023Grounding Graph Network Simulators using Physical Sensor Observations
976. ICLR 2023Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion
977. ICLR 2023Imitating Graph-Based Planning with Goal-Conditioned Policies
978. ICLR 2023Interpretable Geometric Deep Learning via Learnable Randomness Injection
979. ICLR 2023Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
980. ICLR 2023Latent Graph Inference using Product Manifolds
981. ICLR 2023Learnable Graph Convolutional Attention Networks
982. ICLR 2023Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks
983. ICLR 2023Learning Fair Graph Representations via Automated Data Augmentations
984. ICLR 2023Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
985. ICLR 2023Learning Hierarchical Protein Representations via Complete 3D Graph Networks
986. ICLR 2023Learning rigid dynamics with face interaction graph networks
987. ICLR 2023LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
988. ICLR 2023Limitless Stability for Graph Convolutional Networks
989. ICLR 2023Link Prediction with Non-Contrastive Learning
990. ICLR 2023LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence
991. ICLR 2023Logical Message Passing Networks with One-hop Inference on Atomic Formulas
992. ICLR 2023MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning
993. ICLR 2023Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
994. ICLR 2023NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
995. ICLR 2023On Compositional Uncertainty Quantification for Seq2seq Graph Parsing
996. ICLR 2023On Representing Linear Programs by Graph Neural Networks
997. ICLR 2023On Representing Mixed-Integer Linear Programs by Graph Neural Networks
998. ICLR 2023Rethinking Graph Lottery Tickets: Graph Sparsity Matters
999. ICLR 2023Rethinking the Expressive Power of GNNs via Graph Biconnectivity
1000. ICLR 2023REVISITING PRUNING AT INITIALIZATION THROUGH THE LENS OF RAMANUJAN GRAPH

FAQ

How many Deep learning · graph neural networks papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,648 in total: 728 in 2023, 297 in 2024, 297 in 2025, 326 in 2026.

How many Deep learning · graph neural networks papers are at NeurIPS 2026?

NeurIPS 2026 has 102 Deep learning · graph neural networks papers, versus 91 the year before.

How many Deep learning · graph neural networks papers are at ICLR 2026?

ICLR 2026 has 32 Deep learning · graph neural networks papers, versus 50 the year before.

How many Deep learning · graph neural networks papers are at ICML 2026?

ICML 2026 has 168 Deep learning · graph neural networks papers, versus 141 the year before.

How many Deep learning · graph neural networks papers are at CVPR 2026?

CVPR 2026 has 24 Deep learning · graph neural networks papers, versus 15 the year before.

Which conference publishes the most Deep learning · graph neural networks papers?

NeurIPS, with 842 papers from 2023 to 2026.