| 2025 | AIES | Steerable Pluralism: Pluralistic Alignment via Few-Shot Comparative Regression. | Jadie Adams, Brian Hu, Emily Veenhuis, David Joy, Bharadwaj Ravichandran, Aaron Bray, Anthony Hoogs, Arslan Basharat |
| 2024 | ICLR | Point2SSM: Learning Morphological Variations of Anatomies from Point Clouds. | Jadie Adams, Shireen Y. Elhabian |
| 2024 | MICCAI | Weakly Supervised Bayesian Shape Modeling from Unsegmented Medical Images. | Jadie Adams, Krithika Iyer, Shireen Y. Elhabian |
| 2024 | MICCAI | Estimation and Analysis of Slice Propagation Uncertainty in 3D Anatomy Segmentation. | Rachaell Nihalaani, Tushar Kataria, Jadie Adams, Shireen Y. Elhabian |
| 2023 | AAAI | Probabilistic Shape Models of Anatomy Directly from Images. | Jadie Adams |
| 2023 | AAAI | Cosmic Microwave Background Recovery: A Graph-Based Bayesian Convolutional Network Approach. | Jadie Adams, Steven Lu, Krzysztof M. Gorski, Graca Rocha, Kiri L. Wagstaff |
| 2023 | MICCAI | Can Point Cloud Networks Learn Statistical Shape Models of Anatomies? | Jadie Adams, Shireen Y. Elhabian |
| 2023 | MICCAI | Fully Bayesian VIB-DeepSSM. | Jadie Adams, Shireen Y. Elhabian |
| 2023 | MICCAI | Benchmarking Scalable Epistemic Uncertainty Quantification in Organ Segmentation. | Jadie Adams, Shireen Y. Elhabian |
| 2023 | MICCAI | Progressive DeepSSM: Training Methodology for Image-To-Shape Deep Models. | Abu Zahid Bin Aziz, Jadie Adams, Shireen Y. Elhabian |
| 2022 | MICCAI | From Images to Probabilistic Anatomical Shapes: A Deep Variational Bottleneck Approach. | Jadie Adams, Shireen Y. Elhabian |
| 2020 | MICCAI | Uncertain-DeepSSM: From Images to Probabilistic Shape Models. | Jadie Adams, Riddhish Bhalodia, Shireen Y. Elhabian |