Awesome
Continual Learning Through Synaptic Intelligence
This repository contains code to reproduce the key findings of our path integral approach to prevent catastrophic forgetting in continual learning.
Zenke, F.<sup>1</sup>, Poole, B.<sup>1</sup>, and Ganguli, S. (2017). Continual Learning Through Synaptic Intelligence. In Proceedings of the 34th International Conference on Machine Learning, D. Precup, and Y.W. Teh, eds. (International Convention Centre, Sydney, Australia: PMLR), pp. 3987–3995.
http://proceedings.mlr.press/v70/zenke17a.html
<sup>1</sup>) Equal contribution
BibTeX
@InProceedings{pmlr-v70-zenke17a,
title = {Continual Learning Through Synaptic Intelligence},
author = {Friedemann Zenke and Ben Poole and Surya Ganguli},
booktitle = {Proceedings of the 34th International Conference on Machine Learning},
pages = {3987--3995},
year = {2017},
editor = {Doina Precup and Yee Whye Teh},
volume = {70},
series = {Proceedings of Machine Learning Research},
address = {International Convention Centre, Sydney, Australia},
month = {06--11 Aug},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v70/zenke17a/zenke17a.pdf},
url = {http://proceedings.mlr.press/v70/zenke17a.html},
}
Requirements
We have tested this maintenance release (v1.1) with the following configuration:
- Python 3.5.2
- Jupyter 4.4.0
- Tensorflow 1.10
- Keras 2.2.2
Kudos to Mitra (https://github.com/MitraDarja) for making our code conform with Keras 2.2.2!
Earlier releases
For the original release (v1.0) we used the following configuration of the libraries which were available at the time:
- Python 3.5.2
- Jupyter 4.3.0
- Tensorflow 1.2.1
- Keras 2.0.5
To revert to such a environment we suggest using virtualenv (https://virtualenv.pypa.io):
virtualenv -p python3 env
source env/bin/activate
pip3 install -vI keras==2.0.5
pip3 install jupyter matplotlib numpy tensorflow-gpu tqdm seaborn