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Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

Overview of attention for book
Cover of 'Explainable AI: Interpreting, Explaining and Visualizing Deep Learning'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Towards Explainable Artificial Intelligence
  3. Altmetric Badge
    Chapter 2 Transparency: Motivations and Challenges
  4. Altmetric Badge
    Chapter 3 Interpretability in Intelligent Systems – A New Concept?
  5. Altmetric Badge
    Chapter 4 Understanding Neural Networks via Feature Visualization: A Survey
  6. Altmetric Badge
    Chapter 5 Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation
  7. Altmetric Badge
    Chapter 6 Unsupervised Discrete Representation Learning
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    Chapter 7 Towards Reverse-Engineering Black-Box Neural Networks
  9. Altmetric Badge
    Chapter 8 Explanations for Attributing Deep Neural Network Predictions
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    Chapter 9 Gradient-Based Attribution Methods
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    Chapter 10 Layer-Wise Relevance Propagation: An Overview
  12. Altmetric Badge
    Chapter 11 Explaining and Interpreting LSTMs
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    Chapter 12 Comparing the Interpretability of Deep Networks via Network Dissection
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    Chapter 13 Gradient-Based Vs. Propagation-Based Explanations: An Axiomatic Comparison
  15. Altmetric Badge
    Chapter 14 The (Un)reliability of Saliency Methods
  16. Altmetric Badge
    Chapter 15 Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation
  17. Altmetric Badge
    Chapter 16 Understanding Patch-Based Learning of Video Data by Explaining Predictions
  18. Altmetric Badge
    Chapter 17 Quantum-Chemical Insights from Interpretable Atomistic Neural Networks
  19. Altmetric Badge
    Chapter 18 Interpretable Deep Learning in Drug Discovery
  20. Altmetric Badge
    Chapter 19 NeuralHydrology – Interpreting LSTMs in Hydrology
  21. Altmetric Badge
    Chapter 20 Feature Fallacy: Complications with Interpreting Linear Decoding Weights in fMRI
  22. Altmetric Badge
    Chapter 21 Current Advances in Neural Decoding
  23. Altmetric Badge
    Chapter 22 Software and Application Patterns for Explanation Methods
Attention for Chapter 1: Towards Explainable Artificial Intelligence
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
10 news outlets
blogs
1 blog
twitter
7 X users

Citations

dimensions_citation
616 Dimensions

Readers on

mendeley
567 Mendeley
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Chapter title
Towards Explainable Artificial Intelligence
Chapter number 1
Book title
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Published in
arXiv, September 2019
DOI 10.1007/978-3-030-28954-6_1
Book ISBNs
978-3-03-028953-9, 978-3-03-028954-6
Authors

Wojciech Samek, Klaus-Robert Müller

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 567 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 567 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 82 14%
Student > Ph. D. Student 79 14%
Researcher 44 8%
Student > Bachelor 43 8%
Lecturer 20 4%
Other 74 13%
Unknown 225 40%
Readers by discipline Count As %
Computer Science 160 28%
Engineering 47 8%
Business, Management and Accounting 22 4%
Social Sciences 11 2%
Medicine and Dentistry 9 2%
Other 75 13%
Unknown 243 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 83. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 July 2022.
All research outputs
#474,548
of 24,099,692 outputs
Outputs from arXiv
#5,921
of 1,020,419 outputs
Outputs of similar age
#10,541
of 344,214 outputs
Outputs of similar age from arXiv
#172
of 28,129 outputs
Altmetric has tracked 24,099,692 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,020,419 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 344,214 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 28,129 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.