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Theo Rashid
┣━━ code for me
┃   ┣━━ probabilistic-programming-packages  - same forecasting model, different PPLs
┃   ┣━━ mortality-statsmodel                - scalable, Bayesian spatiotemporal models for mortality
┃   ┣━━ bayesian-envhealth-models           - Bayesian models for environmental health
┃   ┗━━ cookiecutter-r-project              - template for analysis project in R
┣━━ code I helped with
┃   ┣━━ numpyro                             - probabilistic programming, jax backend
┃   ┣━━ pymc                                - probabilistic programming, pytensor backend
┃   ┣━━ pytensor                            - python C/jax/numba tensor library
┃   ┗━━ bayeux                              - inference for Bayesian models in jax
┣━━ code I would like to work on
┃   ┣━━ blackjax                            - samplers in jax
┃   ┣━━ dynamax                             - state space models in jax
┃   ┣━━ GPJax                               - Gaussian processes in jax
┃   ┗━━ nimble                              - probabilistic programming in R, customisable samplers
┗━━ work
    ┣━━ Faculty                             - Data Science Fellow
    ┣━━ Amazon                              - Applied Scientist intern, probabilistic forecasting
    ┗━━ Imperial College London
        ┣━━ PhD, Biostatistics              - Scalable spatiotemporal mortality modelling
        ┃   ┣━━ thesis                      - thesis, written in quarto
        ┃   ┗━━ thesis-analysis             - code for postprocessing and plotting in thesis
        ┗━━ MSci, Theoretical Physics       - Mostly maths

Follow me on twitter @theorashid

theorashid's Projects

aesara icon aesara

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

bayeux icon bayeux

State of the art inference for your bayesian models.

beyond-borders icon beyond-borders

Evaluating the suitability of spatial adjacency for small-area estimation

cv icon cv

CV in a readable quarto file and use CSS to publish/print it

gpjax icon gpjax

A didactic Gaussian process package for researchers in Jax.

jax-vae icon jax-vae

Variational autoencoders on categorical and continuous data using jax

kronecker-gp icon kronecker-gp

Implementation of Kronecker inference for Gaussian Processes

nimble icon nimble

Walkthrough of the tutorial chapters for NIMBLE for R

numpyro icon numpyro

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

pymc icon pymc

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

pymc-examples icon pymc-examples

Examples of PyMC models, including a library of Jupyter notebooks.

pytensor icon pytensor

PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

statml icon statml

Lab sessions from the Machine Learning course by Dr Sarah Filippi at Imperial College London

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