Research map / Adversarial robustness and security / Certified and empirical robustness
Efficient Training of Low-Curvature Neural Networks
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
- Compositional Curvature Bounds for Deep Neural Networks (ICML 2024 · similarity 0.88)
- Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon (NeurIPS 2025 · similarity 0.87)
- Global curvature for second-order optimization of neural networks (ICML 2025 · similarity 0.87)
- Towards Adversarially Robust Dataset Distillation by Curvature Regularization (AAAI 2025 · similarity 0.85)
- Improving Neural Network Surface Processing with Principal Curvatures (NeurIPS 2024 · similarity 0.85)
- Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature (NeurIPS 2024 · similarity 0.85)
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.
