New Results
Robust adaptive distance functions for approximate Bayesian inference on outlier-corrupted data
View ORCID ProfileYannik Schälte, View ORCID ProfileEmad Alamoudi, View ORCID ProfileJan Hasenauer
doi: https://doi.org/10.1101/2021.07.29.454327
Yannik Schälte
1Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
2Center for Mathematics, Technische Universität München, 85748 Garching, Germany
Emad Alamoudi
3Faculty of Mathematics and Natural Sciences, Rheinische Friedrich-Wilhelms-Universität Bonn, 53115 Bonn, Germany
Jan Hasenauer
1Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
2Center for Mathematics, Technische Universität München, 85748 Garching, Germany
3Faculty of Mathematics and Natural Sciences, Rheinische Friedrich-Wilhelms-Universität Bonn, 53115 Bonn, Germany
Posted July 30, 2021.
Robust adaptive distance functions for approximate Bayesian inference on outlier-corrupted data
Yannik Schälte, Emad Alamoudi, Jan Hasenauer
bioRxiv 2021.07.29.454327; doi: https://doi.org/10.1101/2021.07.29.454327
Subject Area
Subject Areas
- Biochemistry (13393)
- Bioengineering (10202)
- Bioinformatics (32603)
- Biophysics (16793)
- Cancer Biology (13866)
- Cell Biology (19695)
- Clinical Trials (138)
- Developmental Biology (10643)
- Ecology (15755)
- Epidemiology (2067)
- Evolutionary Biology (20062)
- Genetics (13248)
- Genomics (18387)
- Immunology (13487)
- Microbiology (31583)
- Molecular Biology (13172)
- Neuroscience (68789)
- Paleontology (510)
- Pathology (2133)
- Pharmacology and Toxicology (3683)
- Physiology (5744)
- Plant Biology (11797)
- Synthetic Biology (3313)
- Systems Biology (8046)
- Zoology (1819)