Sana Tonekaboni
According to our database1,
Sana Tonekaboni
authored at least 24 papers
between 2017 and 2025.
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Bibliography
2025
CoRR, June, 2025
When Style Breaks Safety: Defending Language Models Against Superficial Style Alignment.
CoRR, June, 2025
HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
The Latentverse: An Open-Source Benchmarking Toolkit for Evaluating Latent Representations.
Proceedings of the Conference on Health, 2025
2024
A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024.
CoRR, 2024
Proceedings of the Machine Learning for Health, 2024
2023
Encoding the Underlying Dynamics of Complex Time Series With a Focus on Healthcare Applications
PhD thesis, 2023
Modeling personalized heart rate response to exercise and environmental factors with wearables data.
npj Digit. Medicine, 2023
RiskFix: Supporting Expert Validation of Predictive Timeseries Models in High-Intensity Settings.
Proceedings of the 25th Eurographics Conference on Visualization, 2023
Proceedings of the Machine Learning for Health, 2023
2022
CoRR, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU.
Proceedings of the Conference on Health, Inference, and Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding.
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
CoRR, 2020
What went wrong and when? Instance-wise feature importance for time-series black-box models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.
Proceedings of the Machine Learning for Healthcare Conference, 2019
2018
Proceedings of the Machine Learning for Healthcare Conference, 2018
2017
Closed-Loop Neurostimulators: A Survey and A Seizure-Predicting Design Example for Intractable Epilepsy Treatment.
IEEE Trans. Biomed. Circuits Syst., 2017