Stereo-image depth reconstruction with different matching costs and matching algorithms in Python using Numpy and Numba
Embedder with binary sparse distributed representation.
Lab experiments of Soft Computing Techniques
Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
CPU-based spiking neural network framework for classification layers employing first-spike coding and supervised STDP training.
Iterative winners-take-all algorithm
A neuroscientific sequence learning model on spiking neural networks with winner-take-all circuits and lateral inhibition. Written using the NEST neural simulator and custom neuron/synapse models.
GUI for winner-take-all clustering implementation
Pythorch implementation of Winner-Take-All Autoencoder
Add a description, image, and links to the winner-take-all topic page so that developers can more easily learn about it.
To associate your repository with the winner-take-all topic, visit your repo's landing page and select "manage topics."