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Repository for "Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective"

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Sampling by diffusion, flows and autoregressive networks

Repository contanings the notebooks and codes to reproduce the results presented in the paper:

"Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective"

Codes

To be able to reproduce the simulations, it is required to have Python 3 installed with the following packages:

  • Numpy
  • Scipy
  • Pandas

The codes for the SE equations, AMP and Sampling are in the folder Codes

Analysis

Inside the folder Analysis we put the Python code necessary to reproduce our simulations

Data

The folder Data contains all the data frames, and files which are needed to run the notebooks in the folder Analysis

Figures

The folder Figures contains all the plots of the paper, obtained directly from the notebooks present in the folder Analysis.

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Repository for "Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective"

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