Max Hinne

This paper extends hierarchical Bayesian regression to model non-Gaussian data with skewness and kurtosis, showing improved performance on neuroimaging datasets.

PhenoScore quantifies phenotypic similarity using AI and HPO data to improve genetic variant interpretation and genotype-phenotype studies.

This paper compares three facial feature extraction methods for diagnosing genetic disorders, finding that VGGFace2 provides the best performance with 0.78 accuracy.

DeNovoCNN is a deep learning tool for de novo variant calling in sequencing data, achieving high recall and precision compared to existing methods.

The paper investigates how mental imagery influences conscious perception by analyzing individual differences in the interaction between imagery and sensory input using a Bayesian hierarchical model.

The paper introduces two nonparametric Bayesian methods for estimating spike-spike and spike-membrane neuronal connectivity using Gaussian process regression and validates them on simulated and real data.