Results for “evidence-tracking”

Track ML experiments with open-source run logging, local or self-hosted dashboards, and media visualization using SwanLab.

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B.

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.