02.01.2020
©Joachim Wendler - stock-adobe.com
MCML Researchers in Highly-Ranked Journals
Nine Papers in 2020 Highlight Scientific Impact
We are happy to announce that MCML researchers are represented in 2020 with nine papers in highly-ranked journals. Congrats to our researchers!
Conditional out-of-distribution generation for unpaired data using transfer VAE.
Bioinformatics 36.Supplement 2. Dec. 2020. DOI
Sampling uncertainty versus method uncertainty: a general framework with applications to omics biomarker selection.
Biometrical Journal 62.3. May. 2020. DOI
Large-scale benchmark study of survival prediction methods using multi-omics data.
Briefings in Bioinformatics. Aug. 2020. DOI
In vivo identification of apoptotic and extracellular vesicle-bound live cells using image-based deep learning.
Journal of Extracellular Vesicles 9.1. Jul. 2020. DOI
Predicting antigen specificity of single T cells based on TCR CDR3 regions.
Molecular Systems Biology 16.8. Aug. 2020. DOI
Generalizing RNA velocity to transient cell states through dynamical modeling.
Nature Biotechnology 38. Aug. 2020. DOI
Targeted pharmacological therapy restores β-cell function for diabetes remission.
Nature Metabolism 2. Feb. 2020. DOI
Predicting single-cell gene expression profiles of imaging flow cytometry data with machine learning.
Nucleic Acids Research 48.20. Nov. 2020. DOI
Predicting personality from patterns of behavior collected with smartphones.
Proceedings of the National Academy of Sciences 117.30. Jul. 2020. DOI
Related
11.05.2026
Cordelia Schmid Featured in Süddeutsche Zeitung
Cordelia Schmid, a member of the MCML Advisory Board, was recently featured in Süddeutsche Zeitung for her work in computer vision and robotics.
08.05.2026
Right Answer, Wrong Reasoning - Is AI Thinking or Cheating?
Can AI cheat without us noticing? Our PI Barbara Plank and her team introduce a new detection method at ICLR 2026.
07.05.2026
MCML Delegation Visit to the UK
MCML delegation visited top U.S. universities to advance AI X-Change and foster collaboration in generative and medical AI.