Research map / Graph learning / Graph self-supervised learning
Heterophily-aware Contrastive Learning for Heterophilic Hypergraphs
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
- H$^2$CL: Heterogeneity-Aware Hypergraph Contrastive Learning for Robust Representation Learning (ICML 2026 · similarity 0.93)
- When Hypergraph Meets Heterophily: New Benchmark Datasets and Baseline (AAAI 2025 · similarity 0.91)
- I’m Me, We’re Us, and I’m Us: Tri-directional Contrastive Learning on Hypergraphs (AAAI 2023 · similarity 0.91)
- HeterSEED: Semantics–Structure Decoupling for Heterogeneous Graph Learning under Heterophily (NeurIPS 2026 · similarity 0.88)
- Hypergraph-enhanced Dual Semi-supervised Graph Classification (ICML 2024 · similarity 0.88)
- Contrastive Auxiliary Learning with Structure Transformation for Heterogeneous Graphs (AAAI 2025 · similarity 0.87)
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.