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Stochastic-Quasi-Newton

This was a project case study on nonlinear optimization. We implemented the Stochastic Quasi-Newton method, the Stochastic Proximal Gradient method and applied both to a dictionary learning problem.

Stochastic-Gradient-Monte-Carlo

Kolmogorov semigroups are a natural way to combine MCMC methods with Stochastic Gradient Descent.

corona

Some curve fitting with the SEIR model

examination-scheduling

This was a project case study on examination scheduling at the TU Munich

mytris

An open source multiplayer tetris game console.

nlp

SMP

Soft Margin Rosenblatt's Perceptron

Sompy

Self-Organizing Maps using Python and Numpy