Robustness of Explainable Artificial Intelligence in Industrial Process Modelling

12 July 2024

Papers citing "Robustness of Explainable Artificial Intelligence in Industrial Process Modelling"

8 / 8 papers shown

Title
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 54 162 0 11 Aug 2020
Evaluating and Aggregating Feature-based Model Explanations Umang Bhatt Adrian Weller J. M. F. Moura XAI 77 223 0 01 May 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 361 42,299 0 03 Dec 2019
On the Robustness of Interpretability Methods David Alvarez-Melis Tommi Jaakkola 70 526 0 21 Jun 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 889 21,815 0 22 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 174 3,865 0 10 Apr 2017
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 613 38,735 0 09 Mar 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 943 16,931 0 16 Feb 2016