12 citations · 21 across the 6 of their papers we have counts for
6 papers
ASAP: Visual Analytics for Identifying and Analyzing Image Patterns in AI-generated Images
Jinbin Huang, Yuki Ueno, Chen Chen +4
Generative image models can produce highly realistic images, raising concerns about potential misuse in creating deceptive content. Current deepfake approaches face several challen…
A Critical Analysis of the Usage of Dimensionality Reduction in Four Domains
Dylan Cashman, Mark Keller, Hyeon Jeon +2
Dimensionality reduction is used as an important tool for unraveling the complexities of high-dimensional datasets in many fields of science, such as cell biology, chemical informa…
DG Comics: Semi-Automatically Authoring Graph Comics for Dynamic Graphs
Joohee Kim, Hyunwook Lee, Duc M. Nguyen +4
Comics are an effective method for sequential data-driven storytelling, especially for dynamic graphs -- graphs whose vertices and edges change over time. However, manually creatin…
MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models
Grace Guo, Lifu Deng, Animesh Tandon +2
The recent prevalence of publicly accessible, large medical imaging datasets has led to a proliferation of artificial intelligence (AI) models for cardiovascular image classificati…
ASAP: Interpretable Analysis and Summarization of AI-generated Image Patterns at Scale
Jinbin Huang, Chen Chen, Aditi Mishra +3
Generative image models have emerged as a promising technology to produce realistic images. Despite potential benefits, concerns grow about its misuse, particularly in generating d…
ConceptExplainer: Interactive Explanation for Deep Neural Networks from a Concept Perspective
Jinbin Huang, Aditi Mishra, Bum Chul Kwon +1
Traditional deep learning interpretability methods which are suitable for model users cannot explain network behaviors at the global level and are inflexible at providing fine-grai…