mlsanityData to 7 Oct 2026

Visual Knowledge Discovery with Artificial Intelligence: Challenges and Future Directions

arXiv 2205.01296 ↗First posted 3 May 2022cs.AIcited by 3

Not on the map. Why?

Abstract (arXiv)

This volume is devoted to the emerging field of Integrated Visual Knowledge Discovery that combines advances in Artificial Intelligence/Machine Learning (AI/ML) and Visualization/Visual Analytics. Chapters included are extended versions of the selected AI and Visual Analytics papers and related symposia at the recent International Information Visualization Conferences (IV2019 and IV2020). AI/ML face a long-standing challenge of explaining models to humans. Models explanation is fundamentally human activity, not only an algorithmic one. In this chapter we aim to present challenges and future directions within the field of Visual Analytics, Visual Knowledge Discovery and AI/ML, and to discuss the role of visualization in visual AI/ML. In addition, we describe progress in emerging Full 2D ML, natural language processing, and AI/ML in multidimensional data aided by visual means.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 15 of its 91 references that are in the map. First posted on arXiv 3 May 2022.

Builds on

15 of 91 references.

References · 15

  1. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,690
  2. 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
  3. 2019Attention is not Explanationcited by 916
  4. 2016Model-Agnostic Interpretability of Machine Learningcited by 219
  5. 2018Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontierscited by 117
  6. 2021Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factorscited by 106
  7. 2017Deep Learning for IoT Big Data and Streaming Analytics: A Surveycited by 59
  8. 2020A Survey of Visual Analytics Techniques for Machine Learningcited by 56
  9. 2018The State of the Art in Integrating Machine Learning into Visual Analyticscited by 24
  10. 2020Survey of explainable machine learning with visual and granular methods beyond quasi-explanationscited by 20
  11. 2019Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projectionscited by 9
  12. 2021Semiotic Aggregation in Deep Learningcited by 4
3 more
  1. 2021Full interpretable machine learning in 2D with inline coordinatescited by 4
  2. 2020Visual Analytics and Human Involvement in Machine Learningcited by 3
  3. 2020MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scalescited by 3

Built on by

Cited by year

Citing papers per year: 2023: 2; 2024: 1.

3 papers.

  1. 2023Interactive Decision Tree Creation and Enhancement with Complete Visualization for Explainable Modelingcited by 1
  2. 2024Information Plane Analysis Visualization in Deep Learning via Transfer Entropycited by 1
  3. 2023Accelerating Convolutional Neural Network Pruning via Spatial Aura Entropycited by 0