Kurt Hornik is affiliated with the Vienna University of Economics and Business in Austria. Their research spans multiple fields, primarily focusing on computer science and mathematics. Within these broader domains, their work is concentrated on subfields such as artificial intelligence, statistics and probability, applied mathematics, algebra and number theory, and finance.
Their scholarly output includes publications in a range of respected venues. Frequent publication platforms include the Journal of Statistical Software, The R Journal, arXiv (Cornell University), Journal of Computational and Graphical Statistics, and Remote Sensing. They have authored papers covering diverse research topics that intersect statistical methodology and computational techniques.
Key topics addressed in their body of work encompass:
Frequent collaborators include Lukas Sablica, Laura Vana, Bettina Grün, Achim Zeileis, and Rainer Hirk, reflecting a network of coauthors engaged in related research areas.
Representative recent papers authored or co-authored by Kurt Hornik include:
The scope of their work combines theoretical and applied perspectives, integrating statistical inference methods with computational tools and machine learning. The range of topics covered spans from Bayesian mixture models to semantic segmentation in satellite imagery, highlighting a multidisciplinary approach.
K. Hornik;M. Stinchcombe;H. White
Robert C Gentleman;Vincent J Carey;Douglas M. Bates;B.M. Bolstad
Kurt Hornik
Torsten Hothorn;Kurt Hornik;Achim Zeileis
Kurt Hornik;Maxwell Stinchcombe;Halbert White
Alexandros Karatzoglou;Alexandros Smola;Kurt Hornik;Achim Zeileis
Achim Zeileis;Friedrich Leisch;Kurt Hornik;Christian Kleiber
P. Baldi;K. Hornik
Torsten Hothorn;Kurt Hornik;Mark A. van de Wiel;Achim Zeileis
Ingo Feinerer;Kurt Hornik;David Meyer
Bettina Grün;Kurt Hornik
Achim Zeileis;Christian Kleiber;Walter Krämer;Kurt Hornik
David Meyer;Friedrich Leisch;Kurt Hornik
K Hornik;M Stinchcombe;H White
Torsten Hothorn;Kurt Hornik;Mark A van de Wiel;Achim Zeileis
Achim Zeileis;Torsten Hothorn;Kurt Hornik
David Meyer;Evgenia Dimitriadou;Kurt Hornik;Andreas Weingessel
David Meyer;Evgenia Dimitriadou;Kurt Hornik;Andreas Weingessel
Alexandros Karatzoglou;David Meyer;Kurt Hornik
K. Hornik
Kurt Hornik;Robert C. Gentleman;Vincent J. Carey;Douglas M. Bates
If you think any of the details on this page are incorrect, let us know.
If you’re considering computer science, there are several related online degrees and career pathways to explore. Many students are attracted to fast degrees online that allow them to enter the job market quickly. These programs can help you build skills rapidly and start earning sooner.
For those interested in cutting-edge technology, degrees in AI are increasingly popular and can lead to high-demand roles in fields such as machine learning, robotics, and data analysis.
Choosing the best majors in college is vital for long-term career growth. Computer Science remains a top choice, but you might also consider majors that complement technology, such as mathematics or information systems.
If you’re looking to further your education with flexibility, consider the easiest online master's degree options. These programs offer a more approachable workload while still enhancing your qualifications and career potential.
Centre national de la recherche scientifique, CNRS
University of Nottingham
Aarhus University
University of Canberra
Rutgers, The State University of New Jersey
University of California, Berkeley
University of Copenhagen
Lawrence Berkeley National Laboratory
National Institutes of Health
University of New South Wales
Microsoft (United States)
University of British Columbia
University of the Basque Country
Complutense University of Madrid
Swiss Federal Institute for Forest, Snow and Landscape Research
University of Notre Dame