Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization

10 April 2019

Papers citing "Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization"

11 / 11 papers shown

Title
Logical Distillation of Graph Neural Networks Alexander Pluska Pascal Welke Thomas Gärtner Sagar Malhotra 30 0 0 11 Jun 2024
Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates Camille Olivia Little Debolina Halder Lina Genevera I. Allen 31 1 0 06 Oct 2023
DINE: Dimensional Interpretability of Node Embeddings Simone Piaggesi Megha Khosla Andre' Panisson Avishek Anand 29 6 0 02 Oct 2023
Scale-Preserving Automatic Concept Extraction (SPACE) Andres Felipe Posada-Moreno Lukas Kreisköther T. Glander Sebastian Trimpe 21 1 0 11 Aug 2023
Interpreting Neural Policies with Disentangled Tree Representations Tsun-Hsuan Wang Wei Xiao Tim Seyde Ramin Hasani Daniela Rus DRL 30 2 0 13 Oct 2022
A Survey of Neural Trees Haoling Li Mingli Song Mengqi Xue Haofei Zhang Jingwen Ye Lechao Cheng Mingli Song AI4CE 20 6 0 07 Sep 2022
NN2Rules: Extracting Rule List from Neural Networks G. R. Lal Varun Mithal 22 2 0 04 Jul 2022
DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees Peter Müller Lukas Faber Karolis Martinkus Roger Wattenhofer 43 8 0 26 May 2022
XAutoML: A Visual Analytics Tool for Understanding and Validating Automated Machine Learning Marc-André Zöller Waldemar Titov T. Schlegel Marco F. Huber HAI 11 9 0 24 Feb 2022
A Survey on the Explainability of Supervised Machine Learning Nadia Burkart Marco F. Huber FaML XAI 25 752 0 16 Nov 2020
ERIC: Extracting Relations Inferred from Convolutions Joe Townsend Theodoros Kasioumis Hiroya Inakoshi NAI FAtt 23 16 0 19 Oct 2020