activity
20212025
most citedKriging Convolutional Networks

81 citations · 135 across the 13 of their papers we have counts for

collaborators

13 papers

cs.LG2025

The Role of Visualization in LLM-Assisted Knowledge Graph Systems: Effects on User Trust, Exploration, and Workflows

Harry Li, Gabriel Appleby, Kenneth Alperin +2

Knowledge graphs (KGs) are powerful data structures, but exploring them effectively remains difficult for even expert users. Large language models (LLMs) are increasingly used to a…

cs.HC2025★ 2 cited

Mitigating LLM Hallucinations with Knowledge Graphs: A Case Study

Harry Li, Gabriel Appleby, Kenneth Alperin +2

High-stakes domains like cyber operations need responsible and trustworthy AI methods. While large language models (LLMs) are becoming increasingly popular in these domains, they s…

cs.CL2024★ 6 cited

LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering

Harry Li, Gabriel Appleby, Ashley Suh

We present LinkQ, a system that leverages a large language model (LLM) to facilitate knowledge graph (KG) query construction through natural language question-answering. Traditiona…

cs.HC2024★ 1 cited

DimBridge: Interactive Explanation of Visual Patterns in Dimensionality Reductions with Predicate Logic

Brian Montambault, Gabriel Appleby, Jen Rogers +3

Dimensionality reduction techniques are widely used for visualizing high-dimensional data. However, support for interpreting patterns of dimension reduction results in the context…

cs.HC2024

A Typology of Decision-Making Tasks for Visualization

Camelia D. Brumar, Sam Molnar, Gabriel Appleby +2

Despite decision-making being a vital goal of data visualization, little work has been done to differentiate decision-making tasks within the field. While visualization task taxono…

cs.HC2024★ 2 cited

A Preliminary Roadmap for LLMs as Assistants in Exploring, Analyzing, and Visualizing Knowledge Graphs

Harry Li, Gabriel Appleby, Ashley Suh

We present a mixed-methods study to explore how large language models (LLMs) can assist users in the visual exploration and analysis of knowledge graphs (KGs). We surveyed and inte…

cs.HC2023

RekomGNN: Visualizing, Contextualizing and Evaluating Graph Neural Networks Recommendations

Camelia D. Brumar, Gabriel Appleby, Jen Rogers +4

Content recommendation tasks increasingly use Graph Neural Networks, but it remains challenging for machine learning experts to assess the quality of their outputs. Visualization s…

cs.LG2023★ 81 cited

Kriging Convolutional Networks

Gabriel Appleby, Linfeng Liu, Li-Ping Liu

Spatial interpolation is a class of estimation problems where locations with known values are used to estimate values at other locations, with an emphasis on harnessing spatial loc…

cs.HC2023★ 32 cited

Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities

Harry Li, Gabriel Appleby, Camelia Daniela Brumar +2

This study presents insights from interviews with nineteen Knowledge Graph (KG) practitioners who work in both enterprise and academic settings on a wide variety of use cases. Thro…

cs.CY2022

Attention is All They Need: Exploring the Media Archaeology of the Computer Vision Research Paper

Samuel Goree, Gabriel Appleby, David Crandall +1

Research papers, in addition to textual documents, are a designed interface through which researchers communicate. Recently, rapid growth has transformed that interface in many fie…

cs.HC2022★ 10 cited

Are Metrics Enough? Guidelines for Communicating and Visualizing Predictive Models to Subject Matter Experts

Ashley Suh, Gabriel Appleby, Erik W. Anderson +3

Presenting a predictive model's performance is a communication bottleneck that threatens collaborations between data scientists and subject matter experts. Accuracy and error metri…

cs.HC2021

UnProjection: Leveraging Inverse-Projections for Visual Analytics of High-Dimensional Data

Mateus Espadoto, Gabriel Appleby, Ashley Suh +6

Projection techniques are often used to visualize high-dimensional data, allowing users to better understand the overall structure of multi-dimensional spaces on a 2D screen. Altho…

cs.LG2021★ 1 cited

HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters

Gabriel Appleby, Mateus Espadoto, Rui Chen +4

Projection algorithms such as t-SNE or UMAP are useful for the visualization of high dimensional data, but depend on hyperparameters which must be tuned carefully. Unfortunately, i…