Nico Goernitz
Nico Goernitz
CTO @ MorphAIs | former PostDoc @ TU-Berlin
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Deep one-class classification
L Ruff, R Vandermeulen, N Goernitz, L Deecke, SA Siddiqui, A Binder, ...
International conference on machine learning, 4393-4402, 2018
Deep semi-supervised anomaly detection
L Ruff, RA Vandermeulen, N Görnitz, A Binder, E Müller, KR Müller, ...
arXiv preprint arXiv:1906.02694, 2019
Toward supervised anomaly detection
N Görnitz, MM Kloft, K Rieck, U Brefeld
Journal of Artificial Intelligence Research (JAIR), 2013
Active learning for network intrusion detection
N Görnitz, M Kloft, K Rieck, U Brefeld
Proceedings of the 2nd ACM workshop on Security and artificial intelligence …, 2009
Hidden markov anomaly detection
N Görnitz, M Braun, M Kloft
International Conference on Machine Learning, 2015
Support Vector Data Descriptions and -Means Clustering: One Class?
N Görnitz, LA Lima, KR Müller, M Kloft, S Nakajima
IEEE transactions on neural networks and learning systems 29 (9), 3994-4006, 2017
Active and semi-supervised data domain description
N Görnitz, M Kloft, U Brefeld
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2009
Hierarchical multitask structured output learning for large-scale sequence segmentation
N Görnitz, C Widmer, G Zeller, A Kahles, G Rätsch, S Sonnenburg
Advances in Neural Information Processing Systems 24, 2011
Feature importance measure for non-linear learning algorithms
MMC Vidovic, N Görnitz, KR Müller, M Kloft
arXiv preprint arXiv:1611.07567, 2016
DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies
B Mieth, A Rozier, JA Rodriguez, MMC Höhne, N Görnitz, KR Müller
NAR genomics and bioinformatics 3 (3), lqab065, 2021
Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data
B Mieth, JRF Hockley, N Görnitz, MMC Vidovic, KR Müller, A Gutteridge, ...
Scientific reports 9 (1), 20353, 2019
Learning and evaluation in presence of non-iid label noise
N Görnitz, A Porbadnigk, A Binder, C Sannelli, M Braun, KR Müller, ...
Artificial Intelligence and Statistics, 293-302, 2014
Efficient Algorithms for Exact Inference in Sequence Labeling SVMs
A Bauer, N Goernitz, F Biegler, KR Mueller, M Kloft
IEEE Transactions on Neural Networks and Learning (TNNLS), 2013
Deep support vector data description for unsupervised and semi-supervised anomaly detection
L Ruff, RA Vandermeulen, N Gornitz, A Binder, E Muller, M Kloft
Proceedings of the ICML 2019 Workshop on Uncertainty and Robustness in Deep …, 2019
Efficient training of graph-regularized multitask SVMs
C Widmer, M Kloft, N Görnitz, G Rätsch
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2012
Porosity estimation by semi-supervised learning with sparsely available labeled samples
LA Lima, N Görnitz, LE Varella, M Vellasco, KR Müller, S Nakajima
Computers & Geosciences 106, 33-48, 2017
Extracting latent brain states—Towards true labels in cognitive neuroscience experiments
AK Porbadnigk, N Görnitz, C Sannelli, A Binder, M Braun, M Kloft, ...
NeuroImage 120, 225-253, 2015
An off-the-shelf approach to authorship attribution
JA Nasir, N Görnitz, U Brefeld
Proceedings of COLING 2014, the 25th International Conference on …, 2014
Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis
VT Sreedharan, SJ Schultheiss, G Jean, A Kahles, R Bohnert, P Drewe, ...
Bioinformatics 30 (9), 1300-1301, 2014
Ensembles of Lasso screening rules
S Lee, N Görnitz, EP Xing, D Heckerman, C Lippert
IEEE transactions on pattern analysis and machine intelligence 40 (12), 2841 …, 2017
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20