Results for "input change"

Equations governing how system states change over time.

Learning a function from input-output pairs (labeled data), optimizing performance on predicting outputs for unseen inputs.

A measurable property or attribute used as model input (raw or engineered), such as age, pixel intensity, or token ID.

Designing input features to expose useful structure (e.g., ratios, lags, aggregations), often crucial outside deep learning.

Studying internal mechanisms or input influence on outputs (e.g., saliency maps, SHAP, attention analysis).

Local surrogate explanation method approximating model behavior near a specific input.

Model that compresses input into latent space and reconstructs it.

Sensitivity of a function to input perturbations.

Identifying abrupt changes in data generation.

Governance of model changes.