A general approach to compute the relevance of middle-level input
features

A general approach to compute the relevance of middle-level input features

16 October 2020

Andrea Apicella

Salvatore Giugliano

Francesco Isgrò

Papers citing "A general approach to compute the relevance of middle-level input features"

14 / 14 papers shown

Title
Understanding Neural Networks via Feature Visualization: A survey Anh Nguyen J. Yosinski Jeff Clune FAtt 63 161 0 18 Apr 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.5K 94,511 0 11 Oct 2018
Explaining Explanations: An Overview of Interpretability of Machine Learning Leilani H. Gilpin David Bau Ben Z. Yuan Ayesha Bajwa Michael A. Specter Lalana Kagal XAI 83 1,855 0 31 May 2018
Local Rule-Based Explanations of Black Box Decision Systems Riccardo Guidotti A. Monreale Salvatore Ruggieri D. Pedreschi Franco Turini F. Giannotti 123 437 0 28 May 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 120 3,938 0 06 Feb 2018
Visual Interpretability for Deep Learning: a Survey Quanshi Zhang Song-Chun Zhu FaML HAI 120 819 0 02 Feb 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 278 2,257 0 24 Jun 2017
The Latin American Giant Observatory: a successful collaboration in Latin America based on Cosmic Rays and computer science domains Hernán Asorey R. Mayo-García L. Núñez M. Pascual A. J. Rubio-Montero M. Suárez-Durán L. A. Torres-Niño 81 5 0 30 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.0K 16,931 0 16 Feb 2016
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model Benjamin Letham Cynthia Rudin Tyler H. McCormick D. Madigan FAtt 60 743 0 05 Nov 2015
Evaluating the visualization of what a Deep Neural Network has learned Wojciech Samek Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller XAI 132 1,191 0 21 Sep 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 230 4,665 0 21 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.4K 100,213 0 04 Sep 2014
Structured Sparse Principal Component Analysis Rodolphe Jenatton G. Obozinski Francis R. Bach 142 353 0 08 Sep 2009