1.8 KiB
1.8 KiB
Method Examples
Methods are the mathematical techniques used to ask "what pixels mattered to this model's decision?" Each produces a fundamentally different visual character.
model: vgg16 · composition: pure_white · colormap: magma · intensity: 0.75 · contrast: 1.5 · threshold: 0.25 · class_index: -1 · input_size: 224 · use_smoothgrad: true · smoothgrad_samples: 25 · method: varies
| Method | Approach | Character |
|---|---|---|
| Vanilla Gradients | Derivative of output w.r.t. each pixel | Raw, noisy, chaotic — every pixel with any influence at all, including spurious ones |
| SmoothGrad | Vanilla Gradients averaged over many noise-perturbed runs | Smoother and more stable than vanilla, but still texture-rich |
| Integrated Gradients | Accumulates gradients along a path from black image → input | Clean, theoretically grounded, highlights semantically meaningful regions. Usually the best starting method. |
| Blur IG | Like IG, but interpolates from a blurred image → sharp input | Focused on edges and structural transitions rather than color/texture. More architectural. |
| Guided IG | IG with an adaptive path that concentrates steps where gradients are largest | Sharpest, highest-contrast results. Most visually striking for portraits. |
| XRAI | Segments image into regions, attributes importance per region rather than per pixel | Patchwork/stained glass aesthetic — very different from gradient methods. Slower. |
Vanilla Gradients 
SmoothGrad 
Integrated Gradients 
Blur IG 
Guided IG 
XRAI 