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Learning interpretable representations of single-cell multi-omics data with multi-output Gaussian processes

Learning representations of single-cell genomics data is challenging due to the nonlinear and often multi-modal nature of the data on one hand and the need for interpretable representations on the other hand. Existing approaches tend to focus either …

Application-driven validation of posteriors in inverse problems

How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning

Disentangling Mean Embeddings for Better Diagnostics of Image Generators

Exploratory analysis of metabolic changes using mass spectrometry data and graph embeddings

Metrics reloaded: recommendations for image analysis validation

Understanding metric-related pitfalls in image analysis validation

Multimodal analysis methods in predictive biomedicine

Better uncertainty calibration via proper scores for classification and beyond

Inflammatory fibroblasts mediate resistance to neoadjuvant therapy in rectal cancer