Stereo-image depth reconstruction with different matching costs and matching algorithms in Python using Numpy and Numba
Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
Embedder with binary sparse distributed representation.
CPU-based spiking neural network framework for classification layers employing first-spike coding and supervised STDP training.
Lab experiments of Soft Computing Techniques
🥇Winner Take All Hash algorithm by J. Yagnik, implemented in Python.
Two-player TicTacToe winner-takes-all with EOS stakes via smart contract
Iterative winners-take-all algorithm
A collection of artificial neuron models. Written in Julia using Jupyter Notebooks
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.
GUI for winner-take-all clustering implementation
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.
Computer vision system that detects and spatially clusters groups of people in static images using a custom-trained Haar Cascade classifier and a Winner-Takes-All network implemented from scratch in MATLAB. Academic project from my Neuro-Fuzzy Systems course at UPIITA–IPN (2023).
Pythorch implementation of Winner-Take-All Autoencoder
MATLAB code for training and simulating the chemical-based image classification network detailed in "Leveraging autocatalytic reactions for chemical-domain image classification"
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