Dylan Cashman

According to our database, Dylan Cashman authored at least 16 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

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

Mateus Espadoto, Gabriel Appleby, Ashley Suh, Dylan Cashman, Mingwei Li, Carlos Scheidegger, Erik W. Anderson, Remco Chang, Alexandru C. Telea

IEEE Trans. Vis. Comput. Graph., 2023

2022

Visualization Guidelines for Model Performance Communication Between Data Scientists and Subject Matter Experts.

Ashley Suh, Gabriel Appleby, Erik W. Anderson, Luca A. Finelli, Remco Chang, Dylan Cashman

CoRR, 2022

Inferential Tasks as an Evaluation Technique for Visualization.

Ashley Suh, Abigail Mosca, Shannon Robinson, Quinn Pham, Dylan Cashman, Alvitta Ottley, Remco Chang

Proceedings of the 24th Eurographics Conference on Visualization, 2022

2021

CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs.

Dylan Cashman, Shenyu Xu, Subhajit Das, Florian Heimerl, Cong Liu, Shah Rukh Humayoun, Michael Gleicher, Alex Endert, Remco Chang

IEEE Trans. Vis. Comput. Graph., 2021

Communicating Performance of Regression Models Using Visualization in Pharmacovigilance.

Ashley Suh, Gabriel Appleby, Erik W. Anderson, Luca A. Finelli, Dylan Cashman

Proceedings of the IEEE Workshop on Visual Analytics in Healthcare, 2021

NeuralCubes: Deep Representations for Visual Data Exploration.

Zhe Wang, Dylan Cashman, Mingwei Li, Jixian Li, Matthew Berger, Joshua A. Levine, Remco Chang, Carlos Scheidegger

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Ablate, Variate, and Contemplate: Visual Analytics for Discovering Neural Architectures.

Dylan Cashman, Adam Perer, Remco Chang, Hendrik Strobelt

IEEE Trans. Vis. Comput. Graph., 2020

Gaggle: Visual Analytics for Model Space Navigation.

Subhajit Das, Dylan Cashman, Remco Chang, Alex Endert

Proceedings of the 45th Graphics Interface Conference 2020, 2020

2019

RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks.

Dylan Cashman, Genevieve Patterson, Abigail Mosca, Nathan Watts, Shannon Robinson, Remco Chang

CoRR, 2019

A User-based Visual Analytics Workflow for Exploratory Model Analysis.

Dylan Cashman, Shah Rukh Humayoun, Florian Heimerl, Kendall Park, Subhajit Das, John Thompson, Bahador Saket, Abigail Mosca, John T. Stasko, Alex Endert, Michael Gleicher, Remco Chang

Comput. Graph. Forum, 2019

BEAMES: Interactive Multimodel Steering, Selection, and Inspection for Regression Tasks.

Subhajit Das, Dylan Cashman, Remco Chang, Alex Endert

IEEE Computer Graphics and Applications, 2019

Defining an Analysis: A Study of Client-Facing Data Scientists.

Abigail Mosca, Shannon Robinson, Meredith Clarke, Rebecca Redelmeier, Sebastian Coates, Dylan Cashman, Remco Chang

Proceedings of the 21st Eurographics Conference on Visualization, 2019

2018

Visual Analytics for Automated Model Discovery.

Dylan Cashman, Shah Rukh Humayoun, Florian Heimerl, Kendall Park, Subhajit Das, John Thompson, Bahador Saket, Abigail Mosca, John T. Stasko, Alex Endert, Michael Gleicher, Remco Chang

CoRR, 2018

NNCubes: Learned Structures for Visual Data Exploration.

Zhe Wang, Dylan Cashman, Mingwei Li, Jixian Li, Matthew Berger, Joshua A. Levine, Remco Chang, Carlos Scheidegger

CoRR, 2018

RNNbow: Visualizing Learning Via Backpropagation Gradients in RNNs.

Dylan Cashman, Genevieve Patterson, Abigail Mosca, Nathan Watts, Shannon Robinson, Remco Chang

IEEE Computer Graphics and Applications, 2018

2017

Efficient Bayesian Detection of Disease Onset in Truncated Medical Data.

Bob Price, Lottie Price, Dylan Cashman, Marzieh Nabi

Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 2017