Explaining the black-box model: A survey of local interpretation methods for deep neural networks

Delay-distribution-dependent state estimation for neural networks under stochastic communication protocol with uncertain transition probabilities

(2020) Jiahui Li et al.   NEURAL NETWORKS

Adversarial Examples: Attacks and Defenses for Deep Learning

(2019) Xiaoyong Yuan et al.   IEEE Transactions on Neural Networks and Learning Systems

Techniques for interpretable machine learning

(2019) Mengnan Du et al.   COMMUNICATIONS OF THE ACM

A Survey of Methods for Explaining Black Box Models

(2018) Riccardo Guidotti et al.   ACM COMPUTING SURVEYS

Explanation in artificial intelligence: Insights from the social sciences

(2018) Tim Miller   ARTIFICIAL INTELLIGENCE

Finite-Time State Estimation for Delayed Neural Networks With Redundant Delayed Channels

(2018) Zhongyi Zhao et al.   IEEE Transactions on Systems Man Cybernetics-Systems

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

(2017) Vijay Badrinarayanan et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Towards Better Analysis of Deep Convolutional Neural Networks

(2017) Mengchen Liu et al.   IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS

Top-Down Neural Attention by Excitation Backprop

(2017) Jianming Zhang et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Explaining nonlinear classification decisions with deep Taylor decomposition

(2017) Grégoire Montavon et al.   PATTERN RECOGNITION

Deep Belief Networks for Quantitative Analysis of a Gold Immunochromatographic Strip

(2016) Nianyin Zeng et al.   Cognitive Computation

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

(2015) Sebastian Bach et al.   PLoS One

Intrinsic images in the wild

(2014) Sean Bell et al.   ACM TRANSACTIONS ON GRAPHICS

Explaining prediction models and individual predictions with feature contributions

(2013) Erik Štrumbelj et al.   KNOWLEDGE AND INFORMATION SYSTEMS