Sana Tonekaboni

According to our database, Sana Tonekaboni authored at least 14 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024.

Dimitris Spathis, Aaqib Saeed, Ali Etemad, Sana Tonekaboni, Stefanos Laskaridis, Shohreh Deldari, Chi Ian Tang, Patrick Schwab, Shyam Tailor

CoRR, 2024

Learning from Time Series under Temporal Label Noise.

Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen

CoRR, 2024

2023

Modeling personalized heart rate response to exercise and environmental factors with wearables data.

Achille Nazaret, Sana Tonekaboni, Gregory Darnell, Shirley You Ren, Guillermo Sapiro, Andrew C. Miller

npj Digit. Medicine, 2023

Dynamic Interpretable Change Point Detection for Physiological Data Analysis.

Jennifer Yu, Tina Behrouzi, Kopal Garg, Anna Goldenberg, Sana Tonekaboni

Proceedings of the Machine Learning for Health, 2023

2022

Time-Varying Correlation Networks for Interpretable Change Point Detection.

Kopal Garg, Sana Tonekaboni, Anna Goldenberg

CoRR, 2022

Learning Unsupervised Representations for ICU Timeseries.

Addison Weatherhead, Robert Greer, Michael-Alice Moga, Mjaye Mazwi, Danny Eytan, Anna Goldenberg, Sana Tonekaboni

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.

Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg

Proceedings of the Conference on Health, Inference, and Learning, 2022

Decoupling Local and Global Representations of Time Series.

Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding.

Sana Tonekaboni, Danny Eytan, Anna Goldenberg

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

What went wrong and when? Instance-wise Feature Importance for Time-series Models.

Sana Tonekaboni, Shalmali Joshi, David Duvenaud, Anna Goldenberg

CoRR, 2020

What went wrong and when? Instance-wise feature importance for time-series black-box models.

Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David Duvenaud, Anna Goldenberg

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.

Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg

Proceedings of the Machine Learning for Healthcare Conference, 2019

2018

Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU.

Sana Tonekaboni, Mjaye Mazwi, Peter Laussen, Danny Eytan, Robert Greer, Sebastian D. Goodfellow, Andrew J. Goodwin, Michael Brudno, Anna Goldenberg

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.

Hossein Kassiri, Sana Tonekaboni, Muhammad Tariqus Salam, Nima Soltani, Karim Abdelhalim, José Luis Pérez Velazquez, Roman Genov

IEEE Trans. Biomed. Circuits Syst., 2017