| Bold: Dataset and metrics for measuring biases in open-ended language generation J Dhamala, T Sun, V Kumar, S Krishna, Y Pruksachatkun, KW Chang, ... Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021 | 337 | 2021 |
| On the intrinsic and extrinsic fairness evaluation metrics for contextualized language representations YT Cao, Y Pruksachatkun, KW Chang, R Gupta, V Kumar, J Dhamala, ... arXiv preprint arXiv:2203.13928, 2022 | 88 | 2022 |
| “I’m fully who I am”: Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation A Ovalle, P Goyal, J Dhamala, Z Jaggers, KW Chang, A Galstyan, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 47 | 2023 |
| Mitigating gender bias in distilled language models via counterfactual role reversal U Gupta, J Dhamala, V Kumar, A Verma, Y Pruksachatkun, S Krishna, ... arXiv preprint arXiv:2203.12574, 2022 | 44 | 2022 |
| Multi-VALUE: A framework for cross-dialectal English NLP C Ziems, W Held, J Yang, J Dhamala, R Gupta, D Yang arXiv preprint arXiv:2212.08011, 2022 | 35 | 2022 |
| Quantifying the uncertainty in model parameters using Gaussian process-based Markov chain Monte Carlo in cardiac electrophysiology J Dhamala, HJ Arevalo, J Sapp, BM Horácek, KC Wu, NA Trayanova, ... Medical image analysis 48, 43-57, 2018 | 35 | 2018 |
| Does robustness improve fairness? approaching fairness with word substitution robustness methods for text classification Y Pruksachatkun, S Krishna, J Dhamala, R Gupta, KW Chang arXiv preprint arXiv:2106.10826, 2021 | 32 | 2021 |
| Generative modeling and inverse imaging of cardiac transmembrane potential S Ghimire, J Dhamala, PK Gyawali, JL Sapp, M Horacek, L Wang Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 30 | 2018 |
| Spatially adaptive multi-scale optimization for local parameter estimation in cardiac electrophysiology J Dhamala, HJ Arevalo, J Sapp, M Horacek, KC Wu, NA Trayanova, ... IEEE transactions on medical imaging 36 (9), 1966-1978, 2017 | 28 | 2017 |
| Embedding high-dimensional bayesian optimization via generative modeling: parameter personalization of cardiac electrophysiological models J Dhamala, P Bajracharya, HJ Arevalo, JL Sapp, BM Horácek, KC Wu, ... Medical image analysis 62, 101670, 2020 | 27 | 2020 |
| High-dimensional bayesian optimization of personalized cardiac model parameters via an embedded generative model J Dhamala, S Ghimire, JL Sapp, BM Horáček, L Wang Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 21 | 2018 |
| Bayesian optimization on large graphs via a graph convolutional generative model: Application in cardiac model personalization J Dhamala, S Ghimire, JL Sapp, BM Horáček, L Wang Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 18 | 2019 |
| Improving generalization of deep networks for inverse reconstruction of image sequences S Ghimire, PK Gyawali, J Dhamala, JL Sapp, M Horacek, L Wang Information Processing in Medical Imaging: 26th International Conference …, 2019 | 15 | 2019 |
| The consortium for electrocardiographic imaging J Coll-Font, J Dhamala, D Potyagaylo, WHW Schulze, JD Tate, ... 2016 Computing in Cardiology Conference (CinC), 325-328, 2016 | 15 | 2016 |
| Learning geometry-dependent and physics-based inverse image reconstruction X Jiang, S Ghimire, J Dhamala, Z Li, PK Gyawali, L Wang Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 12 | 2020 |
| Overcoming barriers to quantification and comparison of electrocardiographic imaging methods: A community-based approach S Ghimire, J Dhamala, J Coll-Font, JD Tate, MS Guillem, DH Brooks, ... 2017 Computing in Cardiology (CinC), 1-4, 2017 | 10 | 2017 |
| Measuring fairness of text classifiers via prediction sensitivity S Krishna, R Gupta, A Verma, J Dhamala, Y Pruksachatkun, KW Chang arXiv preprint arXiv:2203.08670, 2022 | 9 | 2022 |
| Fast Posterior Estimation of Cardiac Electrophysiological Model Parameters via Bayesian Active Learning MS Zaman, J Dhamala, P Bajracharya, JL Sapp, BM Horácek, KC Wu, ... Frontiers in Physiology 12, 740306, 2021 | 9 | 2021 |
| Quantifying the uncertainty in model parameters using gaussian process-based markov chain monte carlo: An application to cardiac electrophysiological models J Dhamala, JL Sapp, M Horacek, L Wang International Conference on Information Processing in Medical Imaging, 223-235, 2017 | 9 | 2017 |
| Spatially-adaptive multi-scale optimization for local parameter estimation: Application in cardiac electrophysiological models J Dhamala, JL Sapp, M Horacek, L Wang International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 9 | 2016 |
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