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Dylan Cashman
Dylan Cashman
Assistant Professor of Computer Science, Brandeis University
Verified email at brandeis.edu - Homepage
Title
Cited by
Cited by
Year
Rnnbow: Visualizing learning via backpropagation gradients in rnns
D Cashman, G Patterson, A Mosca, N Watts, S Robinson, R Chang
IEEE Computer Graphics and Applications 38 (6), 39-50, 2018
592018
A User‐based Visual Analytics Workflow for Exploratory Model Analysis
D Cashman, SR Humayoun, F Heimerl, K Park, S Das, J Thompson, ...
Computer Graphics Forum 38 (3), 185-199, 2019
58*2019
Beames: Interactive multimodel steering, selection, and inspection for regression tasks
S Das, D Cashman, R Chang, A Endert
IEEE computer graphics and applications 39 (5), 20-32, 2019
452019
Ablate, variate, and contemplate: Visual analytics for discovering neural architectures
D Cashman, A Perer, R Chang, H Strobelt
IEEE transactions on visualization and computer graphics 26 (1), 863-873, 2019
342019
Neuralcubes: Deep representations for visual data exploration
Z Wang, D Cashman, M Li, J Li, M Berger, JA Levine, R Chang, ...
2021 IEEE international conference on big data (big data), 550-561, 2021
27*2021
Cava: A visual analytics system for exploratory columnar data augmentation using knowledge graphs
D Cashman, S Xu, S Das, F Heimerl, C Liu, SR Humayoun, M Gleicher, ...
IEEE Transactions on Visualization and Computer Graphics 27 (2), 1731-1741, 2020
212020
White (but not Black) Americans continue to see racism as a zero-sum game; White conservatives (but not moderates or liberals) see themselves as losing
R Rasmussen, DE Levari, M Akhtar, CS Crittle, M Gately, J Pagan, ...
Perspectives on Psychological Science 17 (6), 1800-1810, 2022
142022
Unprojection: Leveraging inverse-projections for visual analytics of high-dimensional data
M Espadoto, G Appleby, A Suh, D Cashman, M Li, CE Scheidegger, ...
IEEE Transactions on Visualization and Computer Graphics, 2021
92021
Inferential tasks as a data-rich evaluation method for visualization
D Cashman, Y Wu, R Chang, A Ottley
EVIVA-ML: IEEE VIS Workshop on EValuation of Interactive VisuAl Machine …, 2019
92019
Defining an Analysis: A Study of Client-Facing Data Scientists.
A Mosca, S Robinson, M Clarke, R Redelmeier, S Coates, D Cashman, ...
EuroVis (Short Papers), 73-77, 2019
92019
Mast: A tool for visualizing CNN model architecture searches
D Cashman, A Perer, H Strobelt
ICLR 2019 Debugging Machine Learning Models Workshop, 2019
32019
Inferential Tasks as an Evaluation Technique for Visualization
A Suh, A Mosca, S Robinson, Q Pham, D Cashman, A Ottley, R Chang
arXiv preprint arXiv:2205.05712, 2022
22022
Gaggle: Visual Analytics for Model Space Navigation
S Das, D Cashman, R Chang, A Endert
Graphics Interface 2020, 2019
22019
Are Metrics Enough? Guidelines for Communicating and Visualizing Predictive Models to Subject Matter Experts
A Suh, G Appleby, EW Anderson, L Finelli, R Chang, D Cashman
IEEE Transactions on Visualization and Computer Graphics, 2023
12023
Communicating Performance of Regression Models Using Visualization in Pharmacovigilance
A Suh, G Appleby, EW Anderson, L Finelli, D Cashman
2021 IEEE Workshop on Visual Analytics in Healthcare (VAHC), 6-13, 2021
2021
Bridging the Human-Machine Gap in Applied Machine Learning with Visual Analytics
D Cashman
Tufts University, 2020
2020
Replicating Norton and Sommers (2011): Do Whites Still See Racism as a Zero Sum Game in 2019?
R Rasmussen, D Levari, M Akhtar, A Brennen, D Cashman, C Crittle, ...
OSF, 2019
2019
CLIPPR: Maximally Informative CLIPped PRojections with Bounding Regions
B Kang, D Cashman, R Chang, J Lijffijt, T De Bie
IEEE VIS, 2018
2018
Efficient Bayesian Detection of Disease Onset in Truncated Medical Data
B Price, L Price, D Cashman, M Nabi
2017 IEEE International Conference on Healthcare Informatics (ICHI), 208-213, 2017
2017
Big Data, Bigger Audience: A Meta-algorithm for Making Machine Learning Actionable for Analysts
D Cashman, S Kelley, D Staheli, C Fulcher, M Procopio, R Chang
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