Home | News

02.01.2022

Tiny logo
Teaser image to MCML Researchers in Highly-Ranked Journals

MCML Researchers in Highly-Ranked Journals

28 Papers in 2022 Highlight Scientific Impact

We are happy to announce that MCML researchers are represented in 2022 with 28 papers in highly-ranked journals. Congrats to our researchers!

M. Schneble • G. Kauermann
Intensity Estimation on Geometric Networks with Penalized Splines.
Annals of Applied Statistics 16.2. Jun. 2022. DOI
R. Foygel Barber • M. DrtonN. Sturma • L. Weihs
Half-trek criterion for identifiability of latent variable models.
Annals of Statistics 50.6. Dec. 2022. DOI
R. Sonabend • A. Bender • S. Vollmer
Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures.
Bioinformatics 38.17. Sep. 2022. DOI GitHub
E. Pretzsch • V. Heinemann • S. Stintzing • A. BenderS. Chen • J. W. Holch • F. O. Hofmann • H. Ren • F. Böschand • H. Küchenhoff • J. Werner • M. K. Angele
EMT-Related Genes Have No Prognostic Relevance in Metastatic Colorectal Cancer as Opposed to Stage II/III: Analysis of the Randomised, Phase III Trial FIRE-3 (AIO KRK 0306; FIRE-3).
Cancers 14.22. Nov. 2022. DOI
W. Hartl • P. Kopper • A. BenderF. Scheipl • A. G. Day • G. Elke • H. Küchenhoff
Protein intake and outcome of critically ill patients: analysis of a large international database using piece-wise exponential additive mixed models.
Critical Care 26.7. Jan. 2022. DOI
Q. Au • J. Herbinger • C. Stachl • B. BischlG. Casalicchio
Grouped Feature Importance and Combined Features Effect Plot.
Data Mining and Knowledge Discovery 36. Jun. 2022. DOI
K. Lotto • T. Nagler • M. Radic
Modeling Stochastic Data Using Copulas for Applications in the Validation of Autonomous Driving.
Electronics 11.24. Dec. 2022. DOI
M. Mittermeier • M. WeigertD. RügamerH. Küchenhoff • R. Ludwig
A deep learning based classification of atmospheric circulation types over Europe: projection of future changes in a CMIP6 large ensemble.
Environmental Research Letters 17.8. Jul. 2022. DOI
M. van Smeden • G. Heinze • B. Van Calster • F. W. Asselbergs • P. E. Vardas • N. Bruining • P. de Jaegere • J. H. Moore • S. Denaxas • A.-L. Boulesteix • K. G. M. Moons
Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease.
European Heart Journal 43.31. Aug. 2022. DOI
K. Baßler • W. Fujii • T. S. Kapellos • E. Dudkin • N. Reusch • A. Horne • B. Reiz • M. D. Luecken • C. Osei-Sarpong • S. Warnat-Herresthal • L. Bonaguro • J. Schulte-Schrepping • A. Wagner • P. Günther • C. Pizarro • T. Schreiber • R. Knoll • L. Holsten • C. Kröger • E. De Domenico • M. Becker • K. Händler • C. T. Wohnhaas • F. Baumgartner • M. Köhler • H. Theis • M. Kraut • M. H. Wadsworth • T. K. Hughes • H. J. Ferreira • E. Hinkley • I. H. Kaltheuner • M. Geyer • C. Thiele • A. K. Shalek • A. Feißt • D. Thomas • H. Dickten • M. Beyer • P. Baum • N. Yosef • A. C. Aschenbrenner • T. Ulas • J. Hasenauer • F. J. Theis • D. Skowasch • J. L. Schultze
Alveolar macrophages in early stage COPD show functional deviations with properties of impaired immune activation.
Frontiers in Immunology 13. Jul. 2022. DOI
N. Palm • F. Stroebl • H. Palm
Parameter Individual Optimal Experimental Design and Calibration of Parametric Models.
IEEE Access 10. Oct. 2022. DOI GitHub
J. MoosbauerM. BinderL. SchneiderF. PfistererM. Becker • M. Lang • L. Kotthoff • B. Bischl
Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers.
IEEE Transactions on Evolutionary Computation 26.6. Oct. 2022. DOI
M. Ali • M. Berrendorf • C. T. Hoyt • L. Vermue • M. Galkin • S. Sharifzadeh • A. Fischer • V. Tresp • J. Lehmann
Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models under a Unified Framework.
IEEE Transactions on Pattern Analysis and Machine Intelligence 44.12. Dec. 2022. DOI GitHub
G. Brasó • O. Cetintas • L. Leal-Taixé
Multi-Object Tracking and Segmentation Via Neural Message Passing.
International Journal of Computer Vision 130.12. Sep. 2022. DOI GitHub
K. E. Riehm • E. Badillo Goicoechea • F. M. Wang • E. Kim • L. R. Aldridge • C. P. Lupton-Smith • R. Presskreischer • T.-H. Chang • S. LaRocca • F. Kreuter • E. A. Stuart
Association of Non-Pharmaceutical Interventions to Reduce the Spread of SARS-CoV-2 With Anxiety and Depressive Symptoms: A Multi-National Study of 43 Countries.
International Journal of Public Health 67. Mar. 2022. DOI
E. Schede • J. Brandt • A. Tornede • M. WeverV. BengsE. Hüllermeier • K. Tierney
A Survey of Methods for Automated Algorithm Configuration.
Journal of Artificial Intelligence Research 75. Oct. 2022. DOI
C. Fritz • G. De Nicola • F. Günther • D. Rügamer • M. Rave • M. Schneble • A. BenderM. Weigert • R. Brinks • A. Hoyer • U. Berger • H. KüchenhoffG. Kauermann
Challenges in Interpreting Epidemiological Surveillance Data – Experiences from Germany.
Journal of Computational and Graphical Statistics 32.3. Dec. 2022. DOI
C. FritzG. Kauermann
On the Interplay of Regional Mobility, Social Connectedness, and the Spread of COVID-19 in Germany.
Journal of the Royal Statistical Society. Series A (Statistics in Society) 185.1. Jan. 2022. DOI
A. Python • A. Bender • M. Blangiardo • J. B. Illian • Y. Lin • B. Liu • T. C. D. Lucas • S. Tan • Y. Wen • D. Svanidze • J. Yin
A downscaling approach to compare COVID-19 count data from databases aggregated at different spatial scales.
Journal of the Royal Statistical Society. Series A (Statistics in Society) 185.1. Jan. 2022. DOI
Z. Liu • Y. Ma • M. Hildebrandt • Y. Ouyang • Z. Xiong
CDARL: a contrastive discriminator-augmented reinforcement learning framework for sequential recommendations.
Knowledge and Information Systems 64. Jul. 2022. DOI
V.-L. Nguyen • M. H. ShakerE. Hüllermeier
How to measure uncertainty in uncertainty sampling for active learning.
Machine Learning 111.1. Jan. 2022. DOI
B. A. Hersbach • D. S. Fischer • G. Masserdotti • D. Deeksha • K. Mojžišová • T. Waltzhöni • D. Rodriguez‐Terrones • M. Heinig • F. J. Theis • M. Götz • S. H. Stricker
Probing cell identity hierarchies by fate titration and collision during direct reprogramming.
Molecular Systems Biology 18.e11129. Sep. 2022. DOI
M. Lotfollahi • M. Naghipourfar • M. D. Luecken • M. Khajavi • M. Büttner • M. Wagenstetter • Z. Avsec • A. Gayoso • N. Yosef • M. Interlandi • S. Rybakov • A. V. Misharin • F. J. Theis
Mapping single-cell data to reference atlases by transfer learning.
Nature Biotechnology 40. Aug. 2022. DOI
G. Palla • H. Spitzer • M. Klein • D. S. Fischer • A. C. Schaar • L. B. Kuemmerle • S. Rybakov • I. L. Ibarra • O. Holmberg • I. Virshup • M. Lotfollahi • S. Richter • F. J. Theis
Squidpy: a scalable framework for spatial omics analysis.
Nature Methods 19. Jan. 2022. DOI
M. Lange • V. Bergen • M. Klein • M. Setty • B. Reuter • M. Bakhti • H. Lickert • M. Ansari • J. Schniering • H. B. Schiller • D. Pe’er • F. J. Theis
CellRank for directed single-cell fate mapping.
Nature Methods 19.2. Jan. 2022. DOI
W. Ghada • E. Casellas • J. Herbinger • A. Garcia-Benadí • L. Bothmann • N. Estrella • J. Bech • A. Menzel
Stratiform and Convective Rain Classification Using Machine Learning Models and Micro Rain Radar.
Remote Sensing 14.18. Sep. 2022. DOI
C. FritzE. DorigattiD. Rügamer
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany.
Scientific Reports 12.3930. Mar. 2022. DOI
S. Kevork • G. Kauermann
Bipartite Exponential Random Graph Models with Nodal Random Effects.
Social Networks 70. Jun. 2022. DOI
#research #top-tier-work #bischl #boulesteix #cremers #drton #huellermeier #kauermann #kreuter #kuechenhoff #leal-taixe #nagler #ruegamer #scheipl #theis #tresp

Related

Tiny logo
Link to MCML at ICDAR 2026

28.08.2026

MCML at ICDAR 2026

MCML researchers are represented with 1 paper at ICDAR 2026.

Read more
Link to Digdeep Podcast: Well-Intentioned but Dangerous – Will AI Regulation Become a Tool for Censorship?

27.08.2026

Digdeep Podcast: Well-Intentioned but Dangerous – Will AI Regulation Become a Tool for Censorship?

In this episode of #digdeep, MCML Junior Member Sarah Ball talks together with Phil Hackemann about AI regulation.

Read more
Link to Transparency for global health aid

26.08.2026

Transparency for Global Health Aid

MCML PI Stefan Feuerriegel and his team use machine learning to uncover disparities in the global allocation of health aid.

Read more
Link to David Rügamer: We Need Uncertainty Quantification

25.08.2026

David Rügamer: We Need Uncertainty Quantification

MCML PI David Rügamer explains why uncertainty quantification is essential for building trustworthy AI and making informed decisions.

Read more
Link to Using Data Science to Personalize Depression Care

24.08.2026

Using Data Science to Personalize Depression Care

Five young researchers explore how data science can contribute to better healthcare as part of DSSGx Munich 2026, supported by MCML.

Read more
Back to Top