Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

AlphaFold 3 inference pipeline.

Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion models.

Python library for working with gaussian processes

A curated list of awesome nanopore analysis tools.

A simple Snakemake profile for Slurm without --cluster-config

Tandem repeat expansion detection or genotyping from long-read alignments

GWAS Tutorial for Beginners

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚

A minimal GPU design in Verilog to learn how GPUs work from the ground up

A deep-dive on the entire history of deep-learning

A miscellaneous set of helper functions, custom distributions, and other utilities that I find useful when using NumPyro in my work

Material workbench for the master-level course CS-E4740 "Federated Learning"

PyTorch tutorials.

Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.

Just me manually working through ppl-pyro

Statistical Rethinking (2nd ed.) with NumPyro

A curated list of awesome Anki add-ons, decks and resources

Simple utility to concatenate .fastq(.gz) files whilst creating a summary of the sequences.

Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.

Nanopore sequence read simulator

Fast and memory efficient genomic range overlaps for R

Stochastic gradient descent from scratch for linear regression

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

A complete computer science study plan to become a software engineer.

Wallace Lab website