Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
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Updated
Aug 17, 2025 - Python
Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
Stereo-image depth reconstruction with different matching costs and matching algorithms in Python using Numpy and Numba
Lab experiments of Soft Computing Techniques
A collection of artificial neuron models. Written in Julia using Jupyter Notebooks
Embedder with binary sparse distributed representation.
CPU-based spiking neural network framework for classification layers employing first-spike coding and supervised STDP training.
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.
Two-player TicTacToe winner-takes-all with EOS stakes via smart contract
Pythorch implementation of Winner-Take-All Autoencoder
Iterative winners-take-all algorithm
GUI for winner-take-all clustering implementation
This project analyzes Mexico’s 2024 federal elections to explore party performance and voting results. It also simulates the U.S. “Winner-Take-All” system to compare how different voting rules affect electoral outcomes.
MATLAB code for training and simulating the chemical-based image classification network detailed in "Leveraging autocatalytic reactions for chemical-domain image classification"
🥇Winner Take All Hash algorithm by J. Yagnik, implemented in Python.
🎥 Implement optimized stereo matching algorithms in Python, including Block Matching, Dynamic Programming, and more for fast and effective 3D vision applications.
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