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bstaber/README.md

Hey there

Projects I'm currently working on:

  • rustineers: A collection of crates to learn Rust with applied sciences. I try to comment and explain my journey in a small book that goes with it.
  • plaid: An open-source project developped by my colleagues.
  • cppxplorers: A C++ mono-repository playground. There's a book I try to fill as well.
  • kernax: A small JAX-based package that implements kernel methods. I've been refactoring that library a bit.
  • pbnn: A code that benchmarks UQ methods for neural networks in JAX and PyTorch. I'm cleaning this up as well.
  • Python lecture notes: Some lecture notes for a lecture I give about implementing algorithms in Python. I'm trying out marp.
  • Marimo notebooks: Some notebooks that go along with the lecture notes. Trying to make nice visual examples.

Experimenting:

  • uv python monorepo: I made a template for a python mono-repository setup with uv. I added all the tools I like to use right now. It can easily be used as a standard repository too.
  • endurance: An example of python playground based on the above template.

Older stuff:

  • TrilinosUQComp: A 3D parallel finite element solver I made during my PhD thesis. It relies on Trilinos and good old Epetra (which is deprecated now). It was my first C++ project, it has several flaws but I was happy with it! Nowadays I would probably use Spack and rewrite the finite element solvers with Kokkos/Tpetra.
  • BaTorch: A code for benchmarking Bayesian neural networks with PyTorch and Hydra We implemented several Bayesian methods for deep neural networks, and kernel-based distances stuff like the maximum mean discrepancy and the kernelized Stein discrepancy. It is outdated but I plan to use Hydra again in another project.

If you're still here, you can visit my goofy website.

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  1. rustineers rustineers Public

    Learn Rust with Applied Sciences!

    Rust 3 1

  2. pbnn pbnn Public

    Uncertainty quantification for neural networks: Bayesian inference algorithms, deep ensembles, MC Dropout, amongst others.

    Python

  3. python-ml-tutorials-marimo python-ml-tutorials-marimo Public template

    Forked from marimo-team/marimo-gh-pages-template

    ML tutorials in Python

    Python 1

  4. cppxplorers cppxplorers Public

    Explorations in C++ for applied sciences

    C++

  5. TrilinosUQComp TrilinosUQComp Public

    PhD thesis codebase from ~2018 that implements distributed 3D FEM, random field models, uncertainty quantification.

    C++

  6. PLAID-lib/plaid PLAID-lib/plaid Public

    PLAID (Physics-Learning AI Datamodel), a flexible and extensible framework for representing and sharing datasets of physics simulations

    Jupyter Notebook 15 4