Model Learning with Personalized Interpretability Estimation (ML-PIE)

13 April 2021

Papers citing "Model Learning with Personalized Interpretability Estimation (ML-PIE)"

7 / 7 papers shown

Title
Differentiable Genetic Programming for High-dimensional Symbolic Regression Peng Zeng Xiaotian Song Andrew Lensen Yuwei Ou Yanan Sun Mengjie Zhang Jiancheng Lv 24 2 0 18 Apr 2023
Why we do need Explainable AI for Healthcare Giovanni Cina Tabea E. Rober Rob Goedhart Ilker Birbil 30 14 0 30 Jun 2022
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning M. Virgolin Eric Medvet T. Alderliesten Peter A. N. Bosman 14 6 0 05 Apr 2022
Evolvability Degeneration in Multi-Objective Genetic Programming for Symbolic Regression Dazhuang Liu M. Virgolin T. Alderliesten Peter A. N. Bosman 25 12 0 14 Feb 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 26 36 0 22 Jan 2022
Contemporary Symbolic Regression Methods and their Relative Performance William La Cava Patryk Orzechowski Bogdan Burlacu Fabrício Olivetti de Francca M. Virgolin Ying Jin M. Kommenda J. Moore 28 247 0 29 Jul 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015