This page lists various software projects that I have worked on. I list mostly research or machine learning related projects. The order is arbitrary with a hint of date based sorting.

For my latest Deep Learning related research I use Keras because I like choice and Keras can be used both as an abstraction layer over Theano, Tensorflow and CNTK and a symbolic graph creating library for the creation of arbitrarily complex neural networks.

Transparent Keras

PyPI - Github

Transparent Keras aims to provide a very simple way to look under the hood during training of Keras models by defining an extra set of outputs that will be returned by train_on_batch or test_on_batch.

Local Feature Aggregation

PyPI - Github

A library that implements methods to aggregate local features (mainly for multimedia) into a single global feature that can be used easily with any classifier.

The library provides scikit-learn BaseEstimators for BOW, VLAD and Fisher Vectors and was used in our 2017 publication Learning Local Feature Aggregation Functions with Backpropagation.


Homepage - Research page

LDA++ is a C++ library and a set of accompanying console applications that enable the inference of various Latent Dirichlet Allocation models.

It was used in the 2016 ACM-MM publication of Fast Supervised LDA and in the research page we provide data and instructions to reproduce our results.

NlpTools (PHP)

Homepage - packagist

NlpTools is a fairly old NLP library written in PHP. It implements a lot general purpose machine learning components, such as classifiers and clustering, in a way that optimizes for readability and extensibility.

Although it is probably not the best choice for deployment to a massively used website, it is widely used with +65K downloads in packagist and +400 stars at Github.