Research map / Label-efficient and robust learning / Recognition and long-tail
Predicting Deep Neural Network Generalization with Perturbation Response Curves
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
- In search of robust measures of generalization (NeurIPS 2020 · similarity 0.89)
- Input Margins Can Predict Generalization Too (AAAI 2024 · similarity 0.88)
- Train longer, generalize better: closing the generalization gap in large batch training of neural networks (NeurIPS 2017 · similarity 0.88)
- Understanding Generalization through Decision Pattern Shift (NeurIPS 2026 · similarity 0.87)
- Do Neural Networks Need Gradient Descent to Generalize? A Theoretical Study (NeurIPS 2025 · similarity 0.86)
- Gradient-Weight Alignment as a Train-Time Proxy for Generalization in Classification Tasks (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.
