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Found 5 papers, 1 papers with code
Multifunctionality in a Connectome-Based Reservoir Computer
Compared to the widely-used Erd\"os-Renyi Reservoir Computer (ERRC), we report that the FFRC exhibits a greater capacity for multifunctionality; is multifunctional across a broader hyperparameter range; and solves the seeing double problem far beyond the previously observed spectral radius limit, wherein the ERRC's dynamics become chaotic.
Using Connectome Features to Constrain Echo State Networks
We report an improvement to the conventional Echo State Network (ESN) across three benchmark chaotic time-series prediction tasks using fruit fly connectome data alone.
Imposing Connectome-Derived Topology on an Echo State Network
We train and validate the FFESN on a chaotic time series prediction task; here we consider four sets of trials with different training input sizes (small, large) and train-validate splits (two variants).
Novelty Search for Deep Reinforcement Learning Policy Network Weights by Action Sequence Edit Metric Distance
In this paper, we introduce and evaluate the use of novelty search over agent action sequences by string edit metric distance as a means for promoting innovation.
On the Generalizability of Linear and Non-Linear Region of Interest-Based Multivariate Regression Models for fMRI Data
In contrast to conventional, univariate analysis, various types of multivariate analysis have been applied to functional magnetic resonance imaging (fMRI) data.
