A systematic review of robustness in deep learning for computer vision: Mind the gap? N Drenkow, N Sani, I Shpitser, M Unberath arXiv preprint arXiv:2112.00639, 2021 | 70 | 2021 |
Convolutional neural network for second metacarpal radiographic osteoporosis screening N Tecle, J Teitel, MR Morris, N Sani, D Mitten, WC Hammert The Journal of Hand Surgery 45 (3), 175-181, 2020 | 31 | 2020 |
Understanding illicit drug use behaviors by mining social media Y Zhou, N Sani, CK Lee, J Luo arXiv preprint arXiv:1604.07096, 2016 | 17 | 2016 |
Explaining the behavior of black-box prediction algorithms with causal learning N Sani, D Malinsky, I Shpitser arXiv preprint arXiv:2006.02482, 2020 | 16 | 2020 |
Fine-grained mining of illicit drug use patterns using social multimedia data from Instagram Y Zhou, N Sani, J Luo 2016 IEEE International Conference on Big Data (Big Data), 1921-1930, 2016 | 13 | 2016 |
Identification and estimation of causal effects defined by shift interventions N Sani, J Lee, I Shpitser Conference on Uncertainty in Artificial Intelligence, 949-958, 2020 | 9 | 2020 |
Multiply robust causal mediation analysis with continuous treatments AE Ghassami, N Sani, Y Xu, I Shpitser arXiv preprint arXiv:2105.09254, 2021 | 6 | 2021 |
A systematic review of robustness in deep learning for computer vision: Mind the gap? arXiv 2021 N Drenkow, N Sani, I Shpitser, M Unberath arXiv preprint arXiv:2112.00639, 0 | 5 | |
A semiparametric approach to interpretable machine learning N Sani, J Lee, R Nabi, I Shpitser arXiv preprint arXiv:2006.04732, 2020 | 4 | 2020 |
Bounding probabilities of causation through the causal marginal problem N Sani, AA Mastakouri, D Janzing arXiv preprint arXiv:2304.02023, 2023 | 1 | 2023 |
Tightening Bounds on Probabilities of Causation By Merging Datasets N Sani, AA Mastakouri arXiv preprint arXiv:2310.08406, 2023 | | 2023 |
Identifying patients at risk for osteoporosis using artificial intelligence on X-rays C Dasilva, J Teitel, N Sani, D Mitten QUALITY OF LIFE RESEARCH 27, S10-S10, 2018 | | 2018 |