Robustness
المتانة
قدرة النموذج أو التمثيل على الحفاظ على أدائه رغم وجود تشويهات أو اضطرابات أو نقص في المُدخلات. التمثيل المتين يلتقط البنية الجوهرية للبيانات لا تفاصيلها السطحية.
The ability of a model or representation to maintain its performance despite perturbations, noise, or missing information in the input. A robust representation captures the essential structure of the data, not its surface-level details.
Also translated asالصلابة، المقاومة للاضطراب
First appears in this corpus in: Extracting and Composing Robust Features with Denoising Autoencoders (2008)
Appears in these papers
- Intriguing Properties of Neural Networks2014in the sky ✦
- Extracting and Composing Robust Features with Denoising Autoencoders2008in the sky ✦
- Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data2024in the sky ✦
- Explaining and Harnessing Adversarial Examples2015in the sky ✦
- Growing Neural Cellular Automata2020in the sky ✦
- Growing Neural Cellular Automata2020in the sky ✦
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation2017in the sky ✦