# How Important Is a Neuron?

Source: [How Important Is a Neuron?](<https://www.sota2.com/research/paper/68fa646b1e209131cea04985>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:04:03.574Z

Authors: Kedar Dhamdhere, Mukund Sundararajan, Qiqi Yan

Published: 2018-05-30T21:26:22.000Z

## Abstract

The problem of attributing a deep network's prediction to its \\emph{input/base} features is well-studied. We introduce the notion of \\emph{conductance} to extend the notion of attribution to the understanding the importance of \\emph{hidden} units.   Informally, the conductance of a hidden unit of a deep network is the \\emph{flow} of attribution via this hidden unit. We use conductance to understand the importance of a hidden unit to the prediction for a specific input, or over a set of inputs. We evaluate the effectiveness of conductance in multiple ways, including theoretical properties, ablation studies, and a feature selection task. The empirical evaluations are done using the Inception network over ImageNet data, and a sentiment analysis network over reviews. In both cases, we demonstrate the effectiveness of conductance in identifying interesting insights about the internal workings of these networks.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1805.12233>)

[PDF](<https://arxiv.org/pdf/1805.12233.pdf>)