graph laplacian

Anomaly as Non-Conformity via Training-Free Graph Laplacian Energy Minimization CVPR 2026 Differentiable Laplacian Matrix Guided Superpixel Segmentation CVPR 2026 GSNR: Graph Smooth Null-Space Representation for Inverse Problems CVPR 2026 Decentralized Asynchronous Optimization with DADAO allows Decoupling and Acceleration JMLR 2025 GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing IJCAI 2025 Generating Graphs via Spectral Diffusion ICLR 2025 Hallucination Detection in LLMs Using Spectral Features of Attention Maps EMNLP 2025 Learning Laplacian Positional Encodings for Heterophilous Graphs AISTATS 2025 LGA-Net: Learning Local and Global Affinities for Sparse Scribble based Image Colorization ICCV 2025 LOCATEdit: Graph Laplacian Optimized Cross Attention for Localized Text-Guided Image Editing ICCV 2025 Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds JMLR 2025 Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data ICML 2025 Spectral Informed Mamba for Robust Point Cloud Processing CVPR 2025 Spectral State Space Model for Rotation-Invariant Visual Representation Learning CVPR 2025 Efficient Graph Laplacian Estimation by Proximal Newton AISTATS 2024 Fermat Distances: Metric Approximation, Spectral Convergence, and Clustering Algorithms JMLR 2024 Graph Geometry-Preserving Autoencoders ICML 2024 Learning Cartesian Product Graphs with Laplacian Constraints AISTATS 2024 On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models NeurIPS 2024 Scalable Algorithms for Individual Preference Stable Clustering AISTATS 2024 A Fractional Graph Laplacian Approach to Oversmoothing NeurIPS 2023 A Learnable Radial Basis Positional Embedding for Coordinate-MLPs AAAI 2023 A Unified Framework for Optimization-Based Graph Coarsening JMLR 2023 Bayesian Spiked Laplacian Graphs JMLR 2023 Deep Laplacian-based Options for Temporally-Extended Exploration ICML 2023