Laborieux-Axel/holomorphic_eqprop

Repository to reproduce the results of the paper "Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations"

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This project helps machine learning researchers understand and reproduce results from a specific paper on 'Holomorphic Equilibrium Propagation'. It takes simulation parameters in JSON files and outputs data and logs detailing neural network dynamics and training outcomes. This is intended for researchers working on advanced machine learning algorithms and their theoretical underpinnings.

No commits in the last 6 months.

Use this if you are a machine learning researcher aiming to validate or build upon the findings of the 'Holomorphic Equilibrium Propagation' paper.

Not ideal if you are looking for a general-purpose machine learning library or a tool for immediate practical application in product development.

machine-learning-research neural-network-theory gradient-estimation computational-neuroscience deep-learning-algorithms
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 12 / 25

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11

Forks

2

Language

Jupyter Notebook

License

MIT

Last pushed

Oct 20, 2024

Commits (30d)

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