2 papers
cs.LG2026
Improved Predictive Performance and Interpretability for Mesomorphic Neural Networks Using Local Fidelity Regularization
Hugo L. Hammer, Vajira Thambawita, Kristoffer Herland Hellton +1
Interpretable Mesomorphic Neural Networks (IMNs) offer a promising framework that combines the predictive power of deep neural networks with the interpretability of linear models.…
stat.ME2025
Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics
Michael A. Riegler, Kristoffer Herland Hellton, Vajira Thambawita +1
Selecting prior distributions in Bayesian statistics is challenging, resource-intensive, and subjective. We analyze using large-language models (LLMs) to suggest suitable, knowledg…