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Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning

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Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning

Description:

A continual learning framework for class incremental learning described in the following paper arXiv. Note, this is work in progress and this code that will be dynamically updated.

This repository currently contains code to run experiments of DGMw on three datasets: MIST, SVHN, ImageNet.

Requirements

Please, find a list with requiered packages and versions in requierements.txt file.

How to obtain support

This project is provided "as-is" and any bug reports are not guaranteed to be fixed.

Running the tests

In orer to start experiemtns, run the script passing the dataset name as argument (mnist/svhn):

python run.py --dataset mnist --method DGMw

Please, change the metaparmeters in the corresponding file cfg/ if needed.

To run on the ImageNet dataset use the run_DGMw_imagenet.py/ script.

License

This project is licensed under SAP Sample Code License Agreement except as noted otherwise in the LICENSE file.

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