Group: Christian Findenig, Thomas Wedenig
This repository contains slides, demos and useful resources that accompany our talk about Probabilistic Programming in the course Computational Intelligence Seminar B.
Here you can find a subset of the most useful resources we used when preparing the talk:
- https://arxiv.org/abs/1809.10756
- https://storage.googleapis.com/deepmind-media/UCLxDeepMind_2020/L11%20-%20UCLxDeepMind%20DL2020.pdf
- https://pyro.ai/examples/svi_part_i.html
- https://pyro.ai/examples/svi_part_ii.html
- https://pyro.ai/examples/svi_part_iii.html
- https://pyro.ai/examples/minipyro.html
- https://book.sciml.ai/notes/16-From_Optimization_to_Probabilistic_Programming/
- https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/methoden-des-maschinellen-lernens/lehre/probabilistic-machine-learning/ (Lecture 5 on MCMC)
- https://colcarroll.github.io/ppl-api/
- https://ermongroup.github.io/cs228-notes/extras/vae/