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@ICB-DCM @emune-dev @bayesflow-org

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arrjon/README.md

Jonas Arruda

PhD Candidate in Mathematics at the University of Bonn
Researcher at the Bonn Center for Mathematics and Life Sciences (BCMLS) and the LIMES Institute

🔬 Research Focus

I work at the interface of machine learning, probability, and biological modeling.
My current projects focus on:

  • Simulation-based inference for mechanistic simulations
  • Scalable Bayesian inference for large hierarchical dynamical systems
  • Diffusion models and amortized inference for interpretable scientific modeling

📄 Selected Publications

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  1. Amortized-NLME-Models Amortized-NLME-Models Public

    Applying amortizing neural posterior estimation for non-linear mixed effects models

    Jupyter Notebook 7

  2. bayesflow-org/bayesflow bayesflow-org/bayesflow Public

    A Python library for amortized Bayesian workflows using generative neural networks.

    Python 615 78

  3. bayesflow-org/awesome-amortized-inference bayesflow-org/awesome-amortized-inference Public

    This is a community-driven collection of resources around amortized inference.

    TeX 49 3

  4. ICB-DCM/pyABC ICB-DCM/pyABC Public

    distributed, likelihood-free inference

    Python 217 45

  5. ICB-DCM/pyPESTO ICB-DCM/pyPESTO Public

    python Parameter EStimation TOolbox

    Python 262 47