| 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 | 50 | 2018 |
| 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 | 27 | 2019 |
| At a glance: Pixel approximate entropy as a measure of line chart complexity G Ryan, A Mosca, R Chang, E Wu IEEE transactions on visualization and computer graphics 25 (1), 872-881, 2018 | 23 | 2018 |
| Impact of cognitive biases on progressive visualization M Procopio, A Mosca, CE Scheidegger, E Wu, R Chang IEEE Transactions on Visualization and Computer Graphics, 2021 | 11 | 2021 |
| Visual analytics for automated model discovery D Cashman, SR Humayoun, F Heimerl, K Park, S Das, J Thompson, ... arXiv preprint arXiv:1809.10782, 2018 | 9 | 2018 |
| Tipping the balance: The Balancing Incentive Program and state progress on rebalancing their long-term services and supports RS Lester, CV Irvin, A Mosca, C Bradnan National Evaluation of the Money Follows the Person (MFP) Demonstration …, 2015 | 6 | 2015 |
| Does interaction improve bayesian reasoning with visualization? A Mosca, A Ottley, R Chang Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021 | 4 | 2021 |
| 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 | 4 | 2019 |
| Predicting phenotype from multi-scale genomic and environment data using neural networks and knowledge graphs AE Thessen, R Bartelme, M Behrisch, EJ Cain, R Chang, I Debnath, ... 2020 ESA Annual Meeting (August 3-6), 2020 | 2 | 2020 |
| 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 | | 2022 |
| A Grammar for Hypothesis-Driven Visual Analysis A Suh, Y Jiang, A Mosca, E Wu, R Chang arXiv preprint arXiv:2204.14267, 2022 | | 2022 |
| Predicting Phenotype from Multi-Scale Genomic and Environment Data using Neural Networks and Knowledge Graphs: An Introduction to the NSF GenoPhenoEnvo Project A Thessen, M Behrisch, E Cain, R Chang, B Heidorn, P Jaiswal, ... Plant and Animal Genome XXVIII Conference (January 11-15, 2020), 2020 | | 2020 |
| How Good is Your Machine Translation? Quality Estimation for Direct User Feedback A Brennen, A Mosca, R Chang, N Lopatina | | |
| Towards Data Science for the Masses: A Study of Data Scientists and their Interactions with Clients A Mosca, S Robinson, M Clarke, R Redelmeier, S Coates, D Cashman, ... | | |
