6 citations · 6 across the 3 of their papers we have counts for
7 papers
Inferential Tasks as an Evaluation Technique for Visualization
Ashley Suh, Ab Mosca, Shannon Robinson +4
Designing suitable tasks for visualization evaluation remains challenging. Traditional evaluation techniques commonly rely on 'low-level' or 'open-ended' tasks to assess the effica…
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…
CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs
Dylan Cashman, Shenyu Xu, Subhajit Das +6
Most visual analytics systems assume that all foraging for data happens before the analytics process; once analysis begins, the set of data attributes considered is fixed. Such sep…
Ablate, Variate, and Contemplate: Visual Analytics for Discovering Neural Architectures
Dylan Cashman, Adam Perer, Remco Chang +1
Deep learning models require the configuration of many layers and parameters in order to get good results. However, there are currently few systematic guidelines for how to configu…
RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks
Dylan Cashman, Genevieve Patterson, Abigail Mosca +3
We present RNNbow, an interactive tool for visualizing the gradient flow during backpropagation training in recurrent neural networks. RNNbow is a web application that displays the…
A User-based Visual Analytics Workflow for Exploratory Model Analysis
Dylan Cashman, Shah Rukh Humayoun, Florian Heimerl +9
Many visual analytics systems allow users to interact with machine learning models towards the goals of data exploration and insight generation on a given dataset. However, in some…