# Visualizing Transfer Learning

arXiv: https://arxiv.org/abs/2007.07628 · HTML: https://mlsanity.com/paper/2007.07628/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jul 2020.

## Built on by (most cited first, 3 of 3)

- [Explaining, Evaluating and Enhancing Neural Networks' Learned Representations](https://mlsanity.com/paper/2202.09374/) (2022)
- [SIM2REALVIZ: Visualizing the Sim2Real Gap in Robot Ego-Pose Estimation](https://mlsanity.com/paper/2109.11801/) (2021)
- [Explainable Supervised Domain Adaptation](https://mlsanity.com/paper/2205.09943/) (2022)

## Abstract (arXiv)

We provide visualizations of individual neurons of a deep image recognition network during the temporal process of transfer learning. These visualizations qualitatively demonstrate various novel properties of the transfer learning process regarding the speed and characteristics of adaptation, neuron reuse, spatial scale of the represented image features, and behavior of transfer learning to small data. We publish the large-scale dataset that we have created for the purposes of this analysis.