Explainability in human–agent systems

Methods for interpreting and understanding deep neural networks

(2018) Grégoire Montavon et al.   DIGITAL SIGNAL PROCESSING

“Stone-less” or Negative Ureteroscopy. A reality in the Endourologic routine or avoidable source of frustration? Estimating the risk Factors for a Negative Ureteroscopy.

(2018) Ioannis katafigiotis et al.   JOURNAL OF ENDOUROLOGY

Visual interpretability for deep learning: a survey

(2018) Quan-shi Zhang et al.   Frontiers of Information Technology & Electronic Engineering

A Survey of Methods for Explaining Black Box Models

(2018) Riccardo Guidotti et al.   ACM COMPUTING SURVEYS

Explaining Explanation, Part 1: Theoretical Foundations

(2017) Robert R. Hoffman et al.   IEEE INTELLIGENT SYSTEMS

Market Interfaces for Electric Vehicle Charging

(2017) Sebastian Stein et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

(2015) Benjamin Letham et al.   Annals of Applied Statistics

NegoChat-A: a chat-based negotiation agent with bounded rationality

(2015) Avi Rosenfeld et al.   AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS

Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation

(2015) Alex Goldstein et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

Human-agent collectives

(2014) N. R. Jennings et al.   COMMUNICATIONS OF THE ACM

Learning Drivers’ Behavior to Improve Adaptive Cruise Control

(2014) Avi Rosenfeld et al.   Journal of Intelligent Transportation Systems

Using sensitivity analysis and visualization techniques to open black box data mining models

(2012) Paulo Cortez et al.   INFORMATION SCIENCES

Explaining the user experience of recommender systems

(2012) Bart P. Knijnenburg et al.   USER MODELING AND USER-ADAPTED INTERACTION

Prototype selection for interpretable classification

(2011) Jacob Bien et al.   Annals of Applied Statistics

Reverse Engineering the Neural Networks for Rule Extraction in Classification Problems

(2011) M. Gethsiyal Augasta et al.   NEURAL PROCESSING LETTERS

Rules extraction from constructively trained neural networks based on genetic algorithms

(2011) Marghny H. Mohamed   NEUROCOMPUTING

Robust discrimination of glioblastomas from metastatic brain tumors on the basis of single-voxel 1H MRS

(2011) A. Vellido et al.   NMR IN BIOMEDICINE

A Novel Multiresolution Spatiotemporal Saliency Detection Model and Its Applications in Image and Video Compression

(2009) Chenlei Guo et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Rule extraction from trained adaptive neural networks using artificial immune systems

(2007) Humar Kahramanli et al.   EXPERT SYSTEMS WITH APPLICATIONS

Predictive data mining in clinical medicine: Current issues and guidelines

(2007) R BELLAZZI et al.   INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS