# Outliers and Anomalies

An outlier, in Tensormorph, is a value or region whose statistics don't match the distribution around it - a single scalar far outside a tensor's typical range, a tile whose absmax dwarfs its neighbors, a channel whose norm is an order of magnitude off from every other channel in the same layer. Unlike [NaN/Inf detection](/docs/inspect-and-analyze/nan-and-inf-detection), which flags an unambiguous invalid value, outlier detection is a statistical judgment - "unusual relative to what's normal here" - so it depends on comparing a candidate region's [tensor statistics](/docs/inspect-and-analyze/tensor-statistics) against a surrounding baseline rather than a fixed threshold.

## Where anomalies get surfaced

The **Problems panel** is where flagged anomalies accumulate across a whole model - NaN/Inf occurrences, statistical outliers, and other checks - as a single navigable list rather than something you have to notice yourself while browsing. `F8` steps to the next flagged anomaly from anywhere in the workbench, jumping the active view directly to it.

## What counts as unusual

Because this is a judgment relative to a baseline, Tensormorph supports more than one comparison scope:

-   **Within-tensor** - a value flagged relative to the rest of the same tensor's distribution (a classic statistical outlier: several standard deviations from the mean, or beyond a percentile threshold).
-   **Within-layer** - a channel or tile flagged relative to its sibling channels/tiles in the same module, which is often more informative than a whole-tensor baseline for catching a single miscalibrated channel.
-   **Across revisions** - a region flagged because it moved further than expected relative to a baseline checkpoint, which overlaps with [weight diff](/docs/compare-and-morph/weight-diff) territory but is framed here as "is this specific change unusual," not just "what changed."

## Visualizing outliers

In the [Matrix/Heatmap](/docs/editors/matrix-and-heatmap-editor) view, an outlier-highlight shading mode colors elements by how far they sit from the local baseline rather than by raw magnitude - useful specifically because a raw-magnitude heatmap can bury a genuinely anomalous small-magnitude value inside a sea of larger, but individually unremarkable, values.

## Related resources

-   [Tensor Statistics](/docs/inspect-and-analyze/tensor-statistics) - the statistics an outlier judgment is computed against.
-   [NaN and Inf Detection](/docs/inspect-and-analyze/nan-and-inf-detection) - the unambiguous special case of an invalid, rather than merely unusual, value.
-   [Expert Similarity](/docs/inspect-and-analyze/expert-similarity) - a related but distinct question: not "is this value unusual" but "are these two regions unusually similar or dissimilar."