no code implementations • 18 Jul 2023 • Daniel Braun, Ashley Suh, Remco Chang, Michael Gleicher, Tatiana von Landesberger
We investigate the ability of individuals to visually validate statistical models in terms of their fit to the data.
1 code implementation • 3 Apr 2023 • Harry Li, Gabriel Appleby, Camelia Daniela Brumar, Remco Chang, Ashley Suh
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.
1 code implementation • 11 May 2022 • Ashley Suh, Gabriel Appleby, Erik W. Anderson, Luca Finelli, Remco Chang, Dylan Cashman
Presenting a predictive model's performance is a communication bottleneck that threatens collaborations between data scientists and subject matter experts.
no code implementations • 2 Nov 2021 • Mateus Espadoto, Gabriel Appleby, Ashley Suh, Dylan Cashman, MingWei Li, Carlos Scheidegger, Erik W Anderson, Remco Chang, Alexandru C Telea
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.
no code implementations • 25 Jun 2021 • Gabriel Appleby, Mateus Espadoto, Rui Chen, Samuel Goree, Alexandru Telea, Erik W Anderson, Remco Chang
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.
1 code implementation • 7 Sep 2020 • Dylan Cashman, Shenyu Xu, Subhajit Das, Florian Heimerl, Cong Liu, Shah Rukh Humayoun, Michael Gleicher, Alex Endert, Remco Chang
In this paper, we present CAVA, a system that integrates data curation and data augmentation with the traditional data exploration and analysis tasks, enabling information foraging in-situ during analysis.
1 code implementation • 30 Jul 2019 • Dylan Cashman, Adam Perer, Remco Chang, Hendrik Strobelt
In this paper, we present Rapid Exploration of Model Architectures and Parameters, or REMAP, a visual analytics tool that allows a model builder to discover a deep learning model quickly via exploration and rapid experimentation of neural network architectures.
no code implementations • 29 Jul 2019 • Dylan Cashman, Genevieve Patterson, Abigail Mosca, Nathan Watts, Shannon Robinson, Remco Chang
RNNbow is a web application that displays the relative gradient contributions from Recurrent Neural Network (RNN) cells in a neighborhood of an element of a sequence.
no code implementations • 27 Sep 2018 • Dylan Cashman, Shah Rukh Humayoun, Florian Heimerl, Kendall Park, Subhajit Das, John Thompson, Bahador Saket, Abigail Mosca, John Stasko, Alex Endert, Michael Gleicher, Remco Chang
We found that our system workflow enabled users to generate complex models, to assess them for various qualities, and to select the most relevant model for their task.