TrustyAI Explainability Toolkit

TrustyAI Explainability Toolkit

26 April 2021

Tommaso Teofili

Rebecca Whitworth

Papers citing "TrustyAI Explainability Toolkit"

15 / 15 papers shown

Title
PyTorch Tabular: A Framework for Deep Learning with Tabular Data Manu Joseph LMTD 48 37 0 28 Apr 2021
Better sampling in explanation methods can prevent dieselgate-like deception Domen Vreš Marko Robnik-Šikonja AAML 33 10 0 26 Jan 2021
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models Ian Tenney James Wexler Jasmijn Bastings Tolga Bolukbasi Andy Coenen ... Ellen Jiang Mahima Pushkarna Carey Radebaugh Emily Reif Ann Yuan VLM 119 195 0 12 Aug 2020
OptiLIME: Optimized LIME Explanations for Diagnostic Computer Algorithms Giorgio Visani Enrico Bagli F. Chesani FAtt 44 60 0 10 Jun 2020
An Extension of LIME with Improvement of Interpretability and Fidelity Sheng Shi Yangzhou Du Wei Fan FAtt 69 8 0 26 Apr 2020
Statistical stability indices for LIME: obtaining reliable explanations for Machine Learning models Giorgio Visani Enrico Bagli F. Chesani A. Poluzzi D. Capuzzo FAtt 37 166 0 31 Jan 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 116 6,251 0 22 Oct 2019
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques Vijay Arya Rachel K. E. Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind ... Karthikeyan Shanmugam Moninder Singh Kush R. Varshney Dennis L. Wei Yunfeng Zhang XAI 64 392 0 06 Sep 2019
The What-If Tool: Interactive Probing of Machine Learning Models James Wexler Mahima Pushkarna Tolga Bolukbasi Martin Wattenberg F. Viégas Jimbo Wilson VLM 79 491 0 09 Jul 2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions Amir-Hossein Karimi Gilles Barthe Borja Balle Isabel Valera 91 321 0 27 May 2019
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 122 3,938 0 06 Feb 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 98 2,348 0 01 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 239 4,249 0 22 Jun 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 184 3,865 0 10 Apr 2017
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 417 18,334 0 27 May 2016