Explores the concept of explainable neural networks and their significance in improving model interpretability, particularly in finance and house price valuation.
Explores the challenges of multiple testing in genomic data analysis, covering error rate control, adjusted p-values, permutation tests, and pitfalls in hypothesis testing.
