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Found 3 papers, 1 papers with code
Using evolutionary computation to optimize task performance of unclocked, recurrent Boolean circuits in FPGAs
In one type of implementation the output nodes are used directly to perform a task and all learning is via evolution of the network's node functions.
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence
We envision a pipeline to utilize large neuroimaging datasets, including maps of the brain which capture neuron and synapse connectivity, to improve machine learning approaches.
Utilizing a null class to restrict decision spaces and defend against neural network adversarial attacks
Owing to this paradigm, learned decision spaces for individual classes span excessively large regions of the input space and include images that have no semantic similarity to images in the training set.
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