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An automated construction of a denoising autoeconder is presented here. It features an open structure both in the generative phase and in the discriminative phase where input features can be automatically added and discarded on the fly and free of the problem- specific threshold.
This code refers to all experiments in our paper "Autonomous Deep Learning: Continual Learning Approach for Dynamic Environments"
Modified version of ADL and DEVDAN: Implement multiple node growing scenario and adaptive synapses pruning