Research map / Label-efficient and robust learning / Zero-/few-shot and meta-learning
Conditional Meta-Learning of Linear Representations
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
- Provable Meta-Learning of Linear Representations (ICML 2021 · similarity 0.92)
- The Advantage of Conditional Meta-Learning for Biased Regularization and Fine Tuning (NeurIPS 2020 · similarity 0.91)
- Statistically and Computationally Efficient Linear Meta-representation Learning (NeurIPS 2021 · similarity 0.90)
- Learning to Learn with Contrastive Meta-Objective (NeurIPS 2025 · similarity 0.88)
- First-order ANIL provably learns representations despite overparametrisation (ICLR 2024 · similarity 0.86)
- Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning (NeurIPS 2025 · 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.