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 | 66* | 2019 |
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, 2019 | 63 | 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 | 48 | 2019 |
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 | 39 | 2019 |
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 | 32 | 2020 |
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 | 30* | 2021 |
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 | 24 | 2022 |
Unprojection: Leveraging inverse-projections for visual analytics of high-dimensional data M Espadoto, G Appleby, A Suh, D Cashman, M Li, C Scheidegger, ... IEEE Transactions on Visualization and Computer Graphics 29 (2), 1559-1572, 2021 | 21 | 2021 |
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 | 9 | 2019 |
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 | 8* | 2023 |
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 | 8 | 2019 |
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 | 3 | 2022 |
Mast: A tool for visualizing CNN model architecture searches D Cashman, A Perer, H Strobelt ICLR 2019 Debugging Machine Learning Models Workshop, 2019 | 3 | 2019 |
Gaggle: Visual Analytics for Model Space Navigation S Das, D Cashman, R Chang, A Endert Graphics Interface 2020, 2020 | 2 | 2020 |
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 |
PAC Learning Or: Why We Should (and Shouldn't) Trust Machine Learning D Cashman | | |