BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations

BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations

5 December 2020

Papers citing "BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations"

19 / 19 papers shown

Title
ExplainReduce: Summarising local explanations via proxies Lauri Seppäläinen Mudong Guo Kai Puolamäki FAtt 57 0 0 17 Feb 2025
Embedding and Extraction of Knowledge in Tree Ensemble Classifiers Wei Huang Xingyu Zhao Xiaowei Huang AAML 34 11 0 16 Oct 2020
What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors Yi-Shan Lin Wen-Chuan Lee Z. Berkay Celik XAI 51 95 0 22 Sep 2020
Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles Xingyu Zhao K. Salako L. Strigini Valentin Robu David Flynn 26 40 0 19 Aug 2020
A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation Sheng Shi Xinfeng Zhang Wei Fan FAtt 19 28 0 18 Feb 2020
ALIME: Autoencoder Based Approach for Local Interpretability Sharath M. Shankaranarayana D. Runje FAtt 7 103 0 04 Sep 2019
DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems Muhammad Rehman Zafar N. Khan FAtt 60 154 0 24 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 66 1,825 0 06 May 2019
Probabilistic Model Checking of Robots Deployed in Extreme Environments Xingyu Zhao Valentin Robu David Flynn F. Dinmohammadi Michael Fisher M. Webster 17 40 0 10 Dec 2018
Explaining Deep Learning Models - A Bayesian Non-parametric Approach Wenbo Guo Sui Huang Yunzhe Tao Masashi Sugiyama Lin Lin BDL 16 47 0 07 Nov 2018
Model Agnostic Supervised Local Explanations Gregory Plumb Denali Molitor Ameet Talwalkar FAtt LRM MILM 67 196 0 09 Jul 2018
On the Robustness of Interpretability Methods David Alvarez-Melis Tommi Jaakkola 30 524 0 21 Jun 2018
Defining Locality for Surrogates in Post-hoc Interpretablity Thibault Laugel X. Renard Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki FAtt 58 80 0 19 Jun 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 89 1,159 0 19 Jun 2018
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 57 2,274 0 30 Oct 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 139 19,796 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 133 16,765 0 16 Feb 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 218 27,231 0 02 Dec 2015
Convolutional Neural Networks at Constrained Time Cost Kaiming He Jian Sun 3DV 51 1,291 0 04 Dec 2014