Manfred Claassen

22 papers A 1B 1Journal 19
YearRankTypeTitle / Venue / Authors
2026 J jnl
Hilbert space methods for approximating multi-output latent variable Gaussian processes.
Stat. Comput.
Soham Mukherjee, Manfred Claassen, Paul-Christian Bürkner
2025 J jnl
DGP-LVM: Derivative Gaussian process latent variable models.
Stat. Comput.
Soham Mukherjee, Manfred Claassen, Paul-Christian Bürkner
2025 J jnl
Effects of segmentation errors on downstream-analysis in highly-multiplexed tissue imaging.
PLoS Comput. Biol.
Matthias Bruhns, Jan T. Schleicher, Maximilian Wirth, Marcello Zago, Sepideh Babaei, Manfred Claassen
2023 J jnl
A review on deep learning applications in highly multiplexed tissue imaging data analysis.
Frontiers Bioinform.
Mohammed Zidane, Ahmad Makky, Matthias Bruhns, Alexander Rochwarger, Sepideh Babaei, Manfred Claassen, Christian M. Schürch
2023 J jnl
Corrigendum: A review on deep learning applications in highly multiplexed tissue imaging data analysis.
Frontiers Bioinform.
Mohammed Zidane, Ahmad Makky, Matthias Bruhns, Alexander Rochwarger, Sepideh Babaei, Manfred Claassen, Christian M. Schürch
2023 J jnl
S
Patterns
Sepideh Babaei, Jonathan Christ, Vivek Sehra, Ahmad Makky, Mohammed Zidane, Kilian Wistuba-Hamprecht, Christian M. Schürch, Manfred Claassen
2022 J jnl
Privacy-preserving federated neural network learning for disease-associated cell classification.
Patterns
Sinem Sav, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Manfred Claassen, Jean-Pierre Hubaux
2022 J jnl
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder.
Bioinform.
Quentin Garrido, Sebastian Damrich, Alexander Jäger, Dario Cerletti, Manfred Claassen, Laurent Najman, Fred A. Hamprecht
2022 J jnl
psupertime: supervised pseudotime analysis for time-series single-cell RNA-seq data.
Bioinform.
Will Macnair, Revant Gupta, Manfred Claassen
2021 J jnl
Latent representation learning in biology and translational medicine.
Patterns
Andreas Kopf, Manfred Claassen
2021 J jnl
Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations on single cell data.
PLoS Comput. Biol.
Andreas Kopf, Vincent Fortuin, Vignesh Ram Somnath, Manfred Claassen
2021 J jnl
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder.
CoRR
Quentin Garrido, Sebastian Damrich, Alexander Jäger, Dario Cerletti, Manfred Claassen, Laurent Najman, Fred A. Hamprecht
2020 J jnl
Dynamic distribution decomposition for single-cell snapshot time series identifies subpopulations and trajectories during iPSC reprogramming.
PLoS Comput. Biol.
Jake P. Taylor-King, Asbjørn Nilsen Riseth, Will Macnair, Manfred Claassen
2019 J jnl
Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations.
CoRR
Andreas Kopf, Vincent Fortuin, Vignesh Ram Somnath, Manfred Claassen
2018 J jnl
Coupling weak and strong supervision for classification of prostate cancer histopathology images.
CoRR
Eirini Arvaniti, Manfred Claassen
2017 J jnl
Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data.
PLoS Comput. Biol.
Andreas Kühne, Urs Mayr, Daniel C. Sévin, Manfred Claassen, Nicola Zamboni
2016 J jnl
Sparse Regression Based Structure Learning of Stochastic Reaction Networks from Single Cell Snapshot Time Series.
PLoS Comput. Biol.
Anna Klimovskaia, Stefan Ganscha, Manfred Claassen
2014 A conf
Markov Network Structure Learning via Ensemble-of-Forests Models.
UAI
Eirini Arvaniti, Manfred Claassen
2011 J jnl
Proteome Coverage Prediction for Integrated Proteomics Datasets.
J. Comput. Biol.
Manfred Claassen, Ruedi Aebersold, Joachim M. Buhmann
2010 — ch.
Design and Validation of Proteome Measurements.
Ausgezeichnete Informatikdissertationen
Manfred Claassen
2010 B conf
Proteome Coverage Prediction for Integrated Proteomics Datasets.
RECOMB
Manfred Claassen, Ruedi Aebersold, Joachim M. Buhmann
2009 J jnl
Proteome coverage prediction with infinite Markov models.
Bioinform.
Manfred Claassen, Ruedi Aebersold, Joachim M. Buhmann