sparse graph

Reconstructing Riemannian Metrics From Random Geometric Graphs COLT 2026 Coreset Spectral Clustering ICLR 2025 CortexDebate: Debating Sparsely and Equally for Multi-Agent Debate ACL 2025 Learning Mean Field Control on Sparse Graphs ICML 2025 Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment ICML 2025 Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs AISTATS 2025 GmGM: a fast multi-axis Gaussian graphical model AISTATS 2024 Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach ICLR 2024 Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness ICML 2024 Uncertainty Quantification of MLE for Entity Ranking with Covariates JMLR 2024 Contextual Stochastic Block Model: Sharp Thresholds and Contiguity JMLR 2023 Implications of sparsity and high triangle density for graph representation learning AISTATS 2023 Learning Sparse Graphon Mean Field Games AISTATS 2023 Limits, approximation and size transferability for GNNs on sparse graphs via graphops NeurIPS 2023 Locally Regularized Sparse Graph by Fast Proximal Gradient Descent UAI 2023 Optimality of Message-Passing Architectures for Sparse Graphs NeurIPS 2023 Thinned random measures for sparse graphs with overlapping communities NeurIPS 2022 A Unified Framework for Spectral Clustering in Sparse Graphs JMLR 2021 Movie Summarization via Sparse Graph Construction AAAI 2021 Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer EMNLP 2021 Information Theoretic Optimal Learning of Gaussian Graphical Models COLT 2020 Scalable Deep Generative Modeling for Sparse Graphs ICML 2020 A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure AISTATS 2019 Planting trees in graphs, and finding them back COLT 2019 Nonparametric Bayesian sparse graph linear dynamical systems AISTATS 2018