Ensembles of Lasso Screening Rules von Lee, Seunghak, Gornitz, Nico, Xing, Eric P., Heckerman, David, Lippert, Christoph

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Extracting latent brain states — Towards true labels in cognitive neuroscience experiments von Porbadnigk, Anne K., Görnitz, Nico, Sannelli, Claudia, Binder, Alexander, Braun, Mikio, Kloft, Marius, Müller, Klaus-Robert

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DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies von Mieth, Bettina, Rozier, Alexandre, Rodriguez, Juan Antonio, Höhne, Marina M C, Görnitz, Nico, Müller, Klaus-Robert

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Oqtans: a multifunctional workbench for RNA-seq data analysis von Sreedharan, Vipin T, Schultheiss, Sebastian J, Jean, Géraldine, Kahles, André, Bohnert, Regina, Drewe, Philipp, Mudrakarta, Pramod, Görnitz, Nico, Zeller, Georg, Rätsch, Gunnar

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Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning von Porbadnigk, Anne K., Gornitz, Nico, Kloft, Marius, Muller, Klaus-Robert

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Support Vector Data Descriptions and k -Means Clustering: One Class? von Gornitz, Nico, Lima, Luiz Alberto, Muller, Klaus-Robert, Kloft, Marius, Nakajima, Shinichi

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Efficient Algorithms for Exact Inference in Sequence Labeling SVMs von Bauer, Alexander, Gornitz, Nico, Biegler, Franziska, Muller, Klaus-Robert, Kloft, Marius

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Optimizing for Measure of Performance in Max-Margin Parsing von Bauer, Alexander, Nakajima, Shinichi, Gornitz, Nico, Muller, Klaus-Robert

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Support Vector Data Descriptions and [Formula Omitted]-Means Clustering: One Class? von Gornitz, Nico, Lima, Luiz Alberto, Klaus-Robert Muller, Kloft, Marius, Nakajima, Shinichi

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SVM2Motif-Reconstructing Overlapping DNA Sequence Motifs by Mimicking an SVM Predictor: e0144782 von Vidovic, Marina M-C, Gornitz, Nico, Mueller, Klaus-Robert, Raetsch, Gunnar, Kloft, Marius

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Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data von Mieth, Bettina, Hockley, James R. F., Görnitz, Nico, Vidovic, Marina M.-C., Müller, Klaus-Robert, Gutteridge, Alex, Ziemek, Daniel

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Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning von Porbadnigk, Anne K, Gornitz, Nico, Kloft, Marius, Muller, Klaus-Robert

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Oqtans: a Galaxy-integrated workflow for quantitative transcriptome analysis from NGS Data von Schultheiss, Sebastian J, Jean, Géraldine, Behr, Jonas, Bohnert, Regina, Drewe, Philipp, Görnitz, Nico, Kahles, André, Mudrakarta, Pramod, Sreedharan, Vipin T, Zeller, Georg, Rätsch, Gunnar

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Active and Semi-supervised Data Domain Description von Görnitz, Nico, Kloft, Marius, Brefeld, Ulf

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Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms von Vidovic, Marina M.-C., Görnitz, Nico, Müller, Klaus-Robert, Rätsch, Gunnar, Kloft, Marius

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Deep Semi-Supervised Anomaly Detection von Ruff, Lukas, Vandermeulen, Robert A, Görnitz, Nico, Binder, Alexander, Müller, Emmanuel, Müller, Klaus-Robert, Kloft, Marius

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Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs von Bauer, Alexander, Nakajima, Shinichi, Görnitz, Nico, Müller, Klaus-Robert

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Unsupervised Detection and Explanation of Latent-class Contextual Anomalies von Kauffmann, Jacob, Montavon, Grégoire, Lima, Luiz Alberto, Nakajima, Shinichi, Müller, Klaus-Robert, Görnitz, Nico

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Feature Importance Measure for Non-linear Learning Algorithms von Vidovic, Marina M. -C, Görnitz, Nico, Müller, Klaus-Robert, Kloft, Marius

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Deep Semi-Supervised Anomaly Detection von Ruff, Lukas, Vandermeulen, Robert A, Görnitz, Nico, Binder, Alexander, Müller, Emmanuel, Klaus-Robert Müller, Kloft, Marius

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