# Recognition Capabilities of a Hopfield Model with Auxiliary Hidden Neurons

arXiv: https://arxiv.org/abs/2101.05247 · HTML: https://mlsanity.com/paper/2101.05247/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jan 2021.

## Built on by (most cited first, 1 of 1)

- [Pattern reconstruction with restricted Boltzmann machines](https://mlsanity.com/paper/2205.07087/) (2022)

## Abstract (arXiv)

We study the recognition capabilities of the Hopfield model with auxiliary hidden layers, which emerge naturally upon a Hubbard-Stratonovich transformation. We show that the recognition capabilities of such a model at zero-temperature outperform those of the original Hopfield model, due to a substantial increase of the storage capacity and the lack of a naturally defined basin of attraction. The modified model does not fall abruptly in a regime of complete confusion when memory load exceeds a sharp threshold.