Moritz Herrmann

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 11

Top Topics

Outlier Detection

High Dimensional Datasets

Manifold Learning

Top Venues

WIREs Data Mining Knowl. Discov.

Briefings Bioinform.

WIREs Data. Mining. Knowl. Discov.

Publications

Moritz Herrmann, Daniyal Kazempour, Fabian Scheipl, Peer Kröger
Enhancing cluster analysis via topological manifold learning. Data Min. Knowl. Discov. 38 (3) (2024)
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
Position: Why We Must Rethink Empirical Research in Machine Learning. CoRR (2024)
Jana Gauss, Fabian Scheipl, Moritz Herrmann
DCSI - An improved measure of cluster separability based on separation and connectedness. CoRR (2023)
Moritz Herrmann, Florian Pfisterer, Fabian Scheipl
A geometric framework for outlier detection in high-dimensional data. WIREs Data. Mining. Knowl. Discov. 13 (3) (2023)
Christina Nießl, Moritz Herrmann, Chiara Wiedemann, Giuseppe Casalicchio, Anne-Laure Boulesteix
Over-optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results. WIREs Data Mining Knowl. Discov. 12 (2) (2022)
Moritz Herrmann, Florian Pfisterer, Fabian Scheipl
A geometric framework for outlier detection in high-dimensional data. CoRR (2022)
Moritz Herrmann, Daniyal Kazempour, Fabian Scheipl, Peer Kröger
Enhancing cluster analysis via topological manifold learning. CoRR (2022)
Moritz Herrmann, Philipp Probst, Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix
Large-scale benchmark study of survival prediction methods using multi-omics data. Briefings Bioinform. 22 (3) (2021)
Moritz Herrmann, Fabian Scheipl
A geometric perspective on functional outlier detection. CoRR (2021)
Moritz Herrmann, Philipp Probst, Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix
Large-scale benchmark study of survival prediction methods using multi-omics data. CoRR (2020)
Moritz Herrmann, Fabian Scheipl
Unsupervised Functional Data Analysis via Nonlinear Dimension Reduction. CoRR (2020)
Joshua Wing Kei Ho, Youngsook L. Jung, Tao Liu, Burak Han Alver, Soohyun Lee, Kohta Ikegami, Kyung-Ah Sohn, Aki Minoda, Michael Y. Tolstorukov, Alex Appert, Stephen C. J. Parker, Tingting Gu, Anshul Kundaje, Nicole C. Riddle, Eric Bishop, Thea A. Egelhofer, Sheng'en Shawn Hu, Artyom A. Alekseyenko, Andreas Rechtsteiner, Dalal Asker, Jason A. Belsky, Sarah K. Bowman, Q. Brent Chen, Ron A.-J. Chen, Daniel S. Day, Yan Dong, Andrea C. Dose, Xikun Duan, Charles B. Epstein, Sevinc Ercan, Elise A. Feingold, Francesco Ferrari, Jacob M. Garrigues, Nils Gehlenborg, Peter J. Good, Psalm Haseley, Daniel He, Moritz Herrmann, Michael M. Hoffman, Tess E. Jeffers, Peter V. Kharchenko, Paulina Kolasinska-Zwierz, Chitra V. Kotwaliwale, Nischay Kumar, Sasha A. Langley, Erica Larschan, Isabel Latorre, Maxwell W. Libbrecht, Xueqiu Lin, Richard Park, Michael J. Pazin, Hoang N. Pham, Annette Plachetka, Bo Qin, Yuri B. Schwartz, Noam Shoresh, Przemyslaw Stempor, Anne Vielle, Chengyang Wang, Christina M. Whittle, Huiling Xue, Robert E. Kingston, Ju Han Kim, Bradley E. Bernstein, Abby F. Dernburg, Vincenzo Pirrotta, Mitzi I. Kuroda, William S. Noble, Thomas D. Tullius, Manolis Kellis, David M. MacAlpine, Susan Strome, Sarah C. R. Elgin, Xiaole Shirley Liu, Jason D. Lieb, Julie Ahringer, Gary H. Karpen, Peter J. Park
Comparative analysis of metazoan chromatin organization Open. Nat. 512 (7515) (2014)