Research map / Label-efficient and robust learning / OOD and anomaly detection
Integrated Latent Heterogeneity and Invariance Learning in Kernel Space
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
- The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing (NeurIPS 2024 · similarity 0.85)
- Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning (NeurIPS 2025 · similarity 0.85)
- Learning with Exact Invariances in Polynomial Time (ICML 2025 · similarity 0.84)
- Sufficient Invariant Learning for Distribution Shift (CVPR 2025 · similarity 0.84)
- Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts (NeurIPS 2024 · similarity 0.84)
- On Statistical Learning Theory for Distributional Inputs (ICML 2024 · similarity 0.84)
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.