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Sarah Alnegheimish
Sarah Alnegheimish
Verified email at mit.edu
Title
Cited by
Cited by
Year
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
A Geiger, D Liu, S Alnegheimish, A Cuesta-Infante, K Veeramachaneni
2020 IEEE International Conference on Big Data (Big Data), 33-43, 2020
2552020
Using natural sentence prompts for understanding biases in language models
S Alnegheimish, A Guo, Y Sun
Proceedings of the 2022 Conference of the North American Chapter of the …, 2022
19*2022
MTV: Visual analytics for detecting, investigating, and annotating anomalies in multivariate time series
D Liu, S Alnegheimish, A Zytek, K Veeramachaneni
Proceedings of the ACM on Human-Computer Interaction 6 (CSCW1), 1-30, 2022
182022
Sintel: A machine learning framework to extract insights from signals
S Alnegheimish, D Liu, C Sala, L Berti-Equille, K Veeramachaneni
Proceedings of the 2022 International Conference on Management of Data, 1855 …, 2022
152022
Cardea: An open automated machine learning framework for electronic health records
S Alnegheimish, N Alrashed, F Aleissa, S Althobaiti, D Liu, M Alsaleh, ...
2020 IEEE 7th International Conference on Data Science and Advanced …, 2020
142020
AER: Auto-encoder with regression for time series anomaly detection
L Wong, D Liu, L Berti-Equille, S Alnegheimish, K Veeramachaneni
2022 IEEE International Conference on Big Data (Big Data), 1152-1161, 2022
122022
Orion–a machine learning framework for unsupervised time series anomaly detection
S Alnegheimish
Massachusetts Institute of Technology, 2022
42022
Single word change is all you need: Designing attacks and defenses for text classifiers
L Xu, S Alnegheimish, L Berti-Equille, A Cuesta-Infante, ...
arXiv preprint arXiv:2401.17196, 2024
12024
Making the End-User a Priority in Benchmarking: OrionBench for Unsupervised Time Series Anomaly Detection
S Alnegheimish, L Berti-Equille, K Veeramachaneni
arXiv preprint arXiv:2310.17748, 2023
2023
Probabilistic Programming Bots in Intuitive Physics Game Play
F Alhasoun, S Alneghiemish
Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 778-783, 2021
2021
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