Research map / Graph learning / Graph algorithms and clustering
Hyperbolic Continuous Structural Entropy for Hierarchical Clustering
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering (NeurIPS 2020 · similarity 0.91)
- LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering (ICML 2024 · similarity 0.90)
- Structural Entropy Based Graph Structure Learning for Node Classification (AAAI 2024 · similarity 0.89)
- SEC: More Accurate Clustering Algorithm via Structural Entropy (AAAI 2024 · similarity 0.88)
- Weighted Embeddings for Low-Dimensional Graph Representation (AAAI 2025 · similarity 0.86)
- Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples (NeurIPS 2026 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.