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Hi there 👋

I work as an ML researcher, currently interested in Bayesian modelling, language models, causal inference, and using ideas from information theory on the above.

I'm also slowly working through the basics of category theory as well as persistent homology. I'd love to understand how ideas from cat. theory map to applied questions, e.g., the work of Fong, Spivak, et al., with Bayesian networks and data manipulations. For persistent homology, I want to see how tools can be used to learn more about how language models tick.

Kosti's Projects

pykov icon pykov

Pykov is a tiny Python module on finite regular Markov chains.

pymaze icon pymaze

A maze generator, solver and visualizer for Python.

qc icon qc

QuickCheck for Python

rng-arnoldc icon rng-arnoldc

A random number generator in ArnoldC. Wouldn't try anything more complicated than picking lotto numbers with it.

setfit icon setfit

Efficient few-shot learning with Sentence Transformers

small-text icon small-text

Active Learning for Text Classification in Python

stan icon stan

Stan development repository (home page is linked below). The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.

todoist-cli icon todoist-cli

Python command line tool to quickly add tasks to projects with due dates.

vimrc icon vimrc

My vimrc configuration - Needs more work.

vortical-mcmc icon vortical-mcmc

An implementation of an irreversible MCMC sampler. See README for references.

webgazer icon webgazer

WebGazer.js: Scalable Webcam EyeTracking Using User Interactions

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