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Continual Learning with Gated Incremental Memories for Sequential Data Processing. IJCNN 2020. Continual Learning with Recurrent Neural Networks (RNNs) inspired by Progressive network architecture.

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AndreaCossu/ContinualLearning-SequentialProcessing

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ContinualLearning with Gated Incremental Memories for sequential data processing

Paper accepted at IJCNN 2020.

MNIST task

Run the script mnist.py with your hyperparameters of choice.

Audioset task

Download bal.h5, eval.h5 and unbal_train.h5 from here and put them in tasks/audioset/data/.
Then, run audioset_task.py with your hyperparameters of choice.

Devanagari task

Download Devanagari dataset from here and put Train and Test folder inside tasks/mnist/data/Devanagari_CL/.
Then, run mnist.py --devanagari with your hyperparameters of choice.

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Continual Learning with Gated Incremental Memories for Sequential Data Processing. IJCNN 2020. Continual Learning with Recurrent Neural Networks (RNNs) inspired by Progressive network architecture.

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machine-learning pytorch recurrent-neural-networks rnn audioset continual-learning

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