DeepSynergy: predicting anti-cancer drug synergy with Deep Learning _{Bioinformatics}

Learning the High-Dimensional Immunogenomic Features That Predict Public and Private Antibody Repertoires _{J Immunol}

Rectified factor networks for biclustering of omics data _{Bioinformatics}

panelcn.MOPS: Copy number detection in targeted NGS panel data for clinical diagnostics _{Human Mutation}

Self-Normalizing Neural Networks _NIPS

GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium _NIPS

Robust Learning by Conditional Independence of Hidden Units _NIPS

DeepSynergy: Prediction of synergies of anti-cancer drugs with Deep Learning _NIPS

Convolutional Neural Networks for Subcellular Protein Localization _NIPS

panelcn.MOPS - a mixture of Poissons model for copy number detection _NIPS

HapRFN: Rectified Factor Networks for identifying short IBD segments _NIPS

Position kernels as a key to making sense of very rare and private single-nucleotide variants _NIPS

Machine Learning-Based Risk Profile Classification: A Case Study for Heart Valve Surgery _NIPS

Deep Learning for Prediction of Synergistic Effects of Anti-cancer Drugs _NIPS

Deep Learning Yields Virtual Assays _NIPS

Toxicity Prediction Using Self-normalizing Networks _NIPS

Machine Learning-Based Individualized Prognosis _{Whitebook Medical Technology}

GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium _arXiv.org

Self-Normalizing Neural Networks _arXiv.org

Repurposed High-Throughput Images Enable Biological Activity Prediction For Drug Discovery _biorxiv.org

Moment Dynamics in Self-Normalising Neural Networks _{Master Thesis}

Analyzing NGS Data with Machine Learning - From IBD Segments to Copy Number Variations _{PhD Thesis}

Comparison of Rare Variant Association Tests on UK10K Whole Genome Sequencing Data _{Master Thesis}

Convolutional LSTM for Next Frame Prediction _{Master Thesis}

About gradient based importance weighting in feed-forward artificial neural networks _{Master Thesis}