Epsilon Scaling - ComfyUI Built-in Node Documentation

Complete documentation for the Epsilon Scaling node in ComfyUI. Learn its inputs, outputs, parameters and usage.

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This node implements the Epsilon Scaling method from the research paper “Elucidating the Exposure Bias in Diffusion Models.” It works by scaling the predicted noise during the sampling process to help reduce exposure bias, which can lead to improved quality in the generated images. This implementation uses the “uniform schedule” recommended by the paper.

Inputs

Parameter	Data Type	Required	Range	Description
model	MODEL	Yes	-	The model to which the epsilon scaling patch will be applied.
scaling_factor	FLOAT	No	0.5 - 1.5	The factor by which the predicted noise is scaled. A value greater than 1.0 reduces the noise, while a value less than 1.0 increases it (default: 1.005).

Outputs

Output Name	Data Type	Description
model	MODEL	A patched version of the input model with the epsilon scaling function applied to its sampling process.