Graphical Models

Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding EMNLP 2024 NALA: an Effective and Interpretable Entity Alignment Method EMNLP 2024 Neural Gaussian Similarity Modeling for Differential Graph Structure Learning AAAI 2024 Neural Markov Random Field for Stereo Matching CVPR 2024 On Sufficient Graphical Models JMLR 2024 On the Expressive Power of Tree-Structured Probabilistic Circuits NeurIPS 2024 Optimal estimation of Gaussian (poly)trees AISTATS 2024 Ordinal Potential-based Player Rating AISTATS 2024 Polynomial Semantics of Tractable Probabilistic Circuits UAI 2024 Provably Powerful Graph Neural Networks for Directed Multigraphs AAAI 2024 Random Walks for Temporal Action Segmentation With Timestamp Supervision WACV 2024 Rethinking and Extending the Probabilistic Inference Capacity of GNNs ICLR 2024 Seeded Graph Matching for the Correlated Gaussian Wigner Model via the Projected Power Method JMLR 2024 Serving MPE Queries on Tensor Networks by Computing Derivatives PGM 2024 Sparse Graphical Linear Dynamical Systems JMLR 2024 Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs AAAI 2024 Stratified GNN Explanations through Sufficient Expansion AAAI 2024 Structural Entropy Based Graph Structure Learning for Node Classification AAAI 2024 Structural Information Enhanced Graph Representation for Link Prediction AAAI 2024 The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks NeurIPS 2024 TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences AAAI 2024 Transfer Learning for Latent Variable Network Models NeurIPS 2024 Transfer learning for tensor Gaussian graphical models JMLR 2024 Unifying Homophily and Heterophily for Spectral Graph Neural Networks via Triple Filter Ensembles NeurIPS 2024 Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification AAAI 2024