Kristoffer Herland Hellton

Improved Predictive Performance and Interpretability for Mesomorphic Neural Networks Using Local Fidelity Regularization

Hugo L. Hammer, Vajira Thambawita, Kristoffer Herland Hellton, Pål Halvorsen

Interpretable Mesomorphic Neural Networks (IMNs) offer a promising framework that combines the predictive power of deep neural networks with the interpretability of linear models. However, the original formulation lacks safeguards to ensure that the learned interpretations are in…Read more