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valiant's Introduction

Neuroidal Model Implementation

Experiments on random graph models primarily drawn from the following paper:

Valiant, L. G. (2005). Memorization and Association on a Realistic Neural Model. Neural Computation, 17, 527–555.

Code from this repository has been used in the following publications:

  • Chowdhury, C. (December 2023). Foundations Of Memory Capacity In Models Of Neural Cognition. Master’s thesis, California Polytechnic State University, San Luis Obispo.

  • Perrine, P. R. (June 2023). Neural Tabula Rasa: Foundations for Realistic Memories and Learning. Master's thesis. California Polytechnic State University, San Luis Obispo.

Basic Instructions

  1. Install miniconda or anaconda
  2. Start a terminal in the Valiant directory
  3. Create a virtual environment: conda env create -f environment.yml
  4. To install new packages:
    • conda install -n gt <packagename>
    • Add them the YAML using conda env export --no-builds > environment.yml
  5. Refresh the kernel list and select the gt kernel in the notebook.
  6. For scripts, make sure you have the correct interpreter set in your editor.

Sublist Model

  1. Make sure Python and NumPy are installed
  2. Run the sublists notebook cells

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