R. Feldbauer, M. Leodolter, C. Plant and A. Flexer, “Fast Approximate Hubness Reduction for Large High-Dimensional Data,” 2018 IEEE International Conference on Big Knowledge (ICBK), Singapore, 2018, pp. 358-367, doi: 10.1109/ICBK.2018.00055 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8588814&isnumber=8588759, also available as technical report (open access).
Roman Feldbauer and Arthur Flexer: A comprehensive empirical comparison of hubness reduction in high-dimensional spaces. Knowledge and Information Systems, 59(1), 137-166, 2019, DOI (open access)
Roman Feldbauer and Arthur Flexer: Centering Versus Scaling for Hubness Reduction. In: Villa A., Masulli P., Pons Rivero A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science, vol 9886. Springer, Cham, 2016. DOI, also available as technical report (open access).
Roshan Puthenkalam, Marcel Hieckel, Xenia Simeone, Chonticha Suwattanasophon, Roman V. Feldbauer, Gerhard F. Ecker and Margot Ernst: Structural studies of GABA A receptor binding sites: Which experimental structure tells us what? Frontiers in Molecular Neuroscience, Volume 9, 16 June 2016. DOI (open access)
Roman Feldbauer, Frederik Schulz, Matthias Horn and Thomas Rattei: Prediction of microbial phenotypes based on comparative genomics. BMC Bioinformatics 16(Suppl 14):S1, 2015. DOI (open access)
Roman Feldbauer, Arthur Flexer, Thomas Rattei: Deep learning for extremely fast protein similarity search. Austrian HPC Meeting, Grundlsee, Austria, 2019, talk.
Roman Feldbauer, Maximilian Leodolter, Claudia Plant, Arthur Flexer: Fast approximate hubness reduction for large high-dimensional data. International Conference on Big Knowledge (ICBK), Singapore, 2018, talk.
Roman Feldbauer, Arthur Flexer, Thomas Rattei: Protein vector representations for fast similarity search. German Conference on Bioinformatics (GCB), Vienna, Austria, 2018, poster.
Roman Feldbauer, Arthur Flexer: Centering versus Scaling for Hubness Reduction. 25th International Conference on Artificial Neural Networks (ICANN), Barcelona, Spain, 2016, talk.
Roman Feldbauer, Frederik Schulz, Matthias Horn, Thomas Rattei: Prediction of microbial phenotypes based on comparative genomics. Research in Computational Molecular Biology – Comparative Genomics (RECOMB-CG), Frankfurt, Germany, 2015, talk.
Roman V. Feldbauer, Roshan Puthenkalam, Chonticha Suwattanasophon, Margot Ernst: Comparative models of GABA A receptors based on homologous pentameric ligand-gated ion channels co-crystallized with ligands. Joint Meeting of the Austrian Pharmacological Society and the Austrian Neuroscience Association (ANA), Vienna, 2013, poster.
Roman Feldbauer: Machine Learning for Microbial Phenotype Prediction. ISBN: 978-3-658-14318-3, DOI, Springer Spektrum, Wiesbaden, Germany, 2016.
- Knowledge-Based Systems (Elsevier), since 2018
- International Joint Conference on Artificial Intelligence (IJCAI), since 2019
- Knowledge and Information Systems (Springer), since 2019