# Weight Thresholding on Complex Networks

arXiv: https://arxiv.org/abs/1806.07479 · HTML: https://mlsanity.com/paper/1806.07479/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2018.

## Built on by (most cited first, 2 of 2)

- [Spectral Neural Graph Sparsification](https://mlsanity.com/paper/2510.27474/) (2025)
- [Generative Modeling of Discrete Latent Structures via Dynamic Policy Gradients](https://mlsanity.com/paper/2606.07400/) (2026)

## Abstract (arXiv)

Weight thresholding is a simple technique that aims at reducing the number of edges in weighted networks that are otherwise too dense for the application of standard graph theoretical methods. We show that the group structure of real weighted networks is very robust under weight thresholding, as it is maintained even when most of the edges are removed. This appears to be related to the correlation between topology and weight that characterizes real networks. On the other hand, the behavior of other properties is generally system dependent.