Fast hierarchical games for image explanations J Teneggi, A Luster, J Sulam IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (4), 4494-4503, 2022 | 17 | 2022 |
How to trust your diffusion model: A convex optimization approach to conformal risk control J Teneggi, M Tivnan, W Stayman, J Sulam International Conference on Machine Learning, 33940-33960, 2023 | 16 | 2023 |
Examination-Level Supervision for Deep Learning–based Intracranial Hemorrhage Detection on Head CT Scans J Teneggi, PH Yi, J Sulam Radiology: Artificial Intelligence 6 (1), e230159, 2023 | 9* | 2023 |
Fitting splines to axonal arbors quantifies relationship between branch order and geometry TL Athey, J Teneggi, JT Vogelstein, DJ Tward, U Mueller, MI Miller Frontiers in Neuroinformatics 15, 704627, 2021 | 6 | 2021 |
Fourier diffusion models: A method to control mtf and nps in score-based stochastic image generation M Tivnan, J Teneggi, TC Lee, R Zhang, K Boedeker, L Cai, GJ Gang, ... IEEE transactions on medical imaging, 2023 | 5 | 2023 |
SHAP-XRT: The Shapley Value Meets Conditional Independence Testing J Teneggi, B Bharti, Y Romano, J Sulam arXiv preprint arXiv:2207.07038, 2022 | 5* | 2022 |
Entropy estimation within in vitro neural-astrocyte networks as a measure of development instability J Teneggi, X Chen, A Balu, C Barrett, G Grisolia, U Lucia, R Dzakpasu Physical Review E 103 (4), 042412, 2021 | 1 | 2021 |
I Bet You Did Not Mean That: Testing Semantic Importance via Betting J Teneggi, J Sulam arXiv preprint arXiv:2405.19146, 2024 | | 2024 |
How to trust your diffusion model: a convex optimization approach to conformal risk control J Sulam, J Teneggi High-Speed Biomedical Imaging and Spectroscopy IX, PC128530Q, 2024 | | 2024 |
Multiple-instance Learning as a Framework to Explain with Shapley Coefficients J Teneggi Johns Hopkins University, 2022 | | 2022 |