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rpatrik96/README.md

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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  1. ima-vae ima-vae Public

    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 ce…

    Jupyter Notebook 22

  2. nl-causal-representations nl-causal-representations Public

    This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (particularly, with Nonlinear ICA) can be used to extract the causa…

    Python 16 2

  3. pytorch-a2c pytorch-a2c Public

    A well-documented A2C written in PyTorch

    Python 49 10

  4. AttA2C AttA2C Public

    Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning

    Jupyter Notebook 25 7

  5. pytorch-lightning-wavenet pytorch-lightning-wavenet Public

    An implementation of WaveNet using PyTorch & PyTorch Lightning

    Python 13 3

  6. llm-non-identifiability llm-non-identifiability Public

    Investigating the non-identifiability of Transformers

    Python 1