stdp-bernoulli-message-passing

This repository contains the implementation for the paper:

"Spike-Timing-Dependent Plasticity for Bernoulli Message Passing"

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📖 Description

In this work, we use Spike-Timing-Dependent Plasticity (STDP) to train networks of spiking neurons based on Leaky Integrate-and-Fire (LIF) models.
The trained networks are able to perform basic logical operations such as:

• AND
• OR
• NOT

By combining these trained nodes, we also implement more complex operations, including:

• Equality (marginalization)
• XOR

Finally, we compare the performance of these STDP-trained spiking networks with numerical results, as illustrated in the figure below:

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📂 Contents

• src/ – Core implementation
• data/ – Stored results and trained weights
• figures/ – Plots and visual results
• README.md – Project description