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This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivalent to optimizing the IMA-regularized log-likelihood under certain assumptions (e.g., small decoder variance).

License: Apache License 2.0

Python 26.47% Shell 1.06% Jupyter Notebook 72.47%
pytorch vae independent-component-analysis pytorch-lightning variational-autoencoder variational-inference disentanglement dsprites ica wandb

ima-vae's Introduction

Hi, I'm Patrik 👋

I am a PhD student with Wieland Brendel, Ferenc Huszár, Matthias Bethge, and Bernhard Schölkopf at the IMPRS-IS/ELLIS programs with research interests in

  • Causal representation learning and
  • Identifiability

I recently (Sep 2021) started a blog on causality, check it out! Even more recently (Nov 2022), I started the The Path to PhD newsletter to share my thoughts and the advice I received during my PhD.

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