Bio I am currently a postdoctoral fellow with the Laboratory for Computational and Statistical Learning (LCSL), hosted at the Center for Biological and Computational Learning (CBCL), Massachusetts Institute of Technology (MIT). In 2013, I received my Ph.D. summa cum laude from the Department for Informatics of the Ludwig-Maximilians-University of Munich under supervision of Volker Tresp. I received a diploma degree with honors in computer science from the Ludwig Maximilian University Munich in 2009.
A list of selected publications in peer-reviewed conferences and journals, as well as book chapter, tutorials, and workshops.
You can also find my publications on Google Scholar
RESCAL is a tensor factorization for large-scale relational learning from Linked Data, multi-relational data and large multigraphs. RESCAL offers state-of-the-art relational learning results combined with high scalability, such that it can be applied to data consisting of millions of entities, hundreds of relations, and billions of known facts.
scikit-tensor is a Python library for multilinear algebra and tensor factorizations. It includes routines to compute factorizations such as the Tucker decomposition, CP, RESCAL and others. The focus of the library lies on easy-to-use code for fast prototyping as well as high performance and scalability.