Khaled Saab

Orcid: 0000-0003-1427-0469

Affiliations:
  • Georgia Institute of Technology, Atlanta, GA, USA
  • Stanford University, CA, USA (former)


According to our database1, Khaled Saab authored at least 25 papers between 2016 and 2024.

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Bibliography

2024
Towards trustworthy seizure onset detection using workflow notes.
npj Digit. Medicine, 2024

2023
A case for reframing automated medical image classification as segmentation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Effectively Modeling Time Series with Simple Discrete State Spaces.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Hungry Hungry Hippos: Towards Language Modeling with State Space Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models.
Proceedings of the Conference on Health, Inference, and Learning, 2023

2022
A multivariate adaptive gradient algorithm with reduced tuning efforts.
Neural Networks, 2022

Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models.
CoRR, 2022

The Importance of Background Information for Out of Distribution Generalization.
CoRR, 2022

Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity.
Proceedings of the Machine Learning for Healthcare Conference, 2022

Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Domino: Discovering Systematic Errors with Cross-Modal Embeddings.
Proceedings of the Tenth International Conference on Learning Representations, 2022

ViLMedic: a framework for research at the intersection of vision and language in medical AI.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022

2021
Setting the boundaries of COVID-19 lockdown relaxation measures.
Libr. Hi Tech, 2021

Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels.
CoRR, 2021

Automated Seizure Detection and Seizure Type Classification From Electroencephalography With a Graph Neural Network and Self-Supervised Pre-Training.
CoRR, 2021

Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Observational Supervision for Medical Image Classification Using Gaze Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
Cross-Modal Data Programming Enables Rapid Medical Machine Learning.
Patterns, 2020

Weak supervision as an efficient approach for automated seizure detection in electroencephalography.
npj Digit. Medicine, 2020

Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy.
CoRR, 2020

2019
Doubly Weak Supervision of Deep Learning Models for Head CT.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Shuffled Linear Regression with Erroneous Observations.
Proceedings of the 53rd Annual Conference on Information Sciences and Systems, 2019

2017
Protecting Bare-Metal Embedded Systems with Privilege Overlays.
Proceedings of the 2017 IEEE Symposium on Security and Privacy, 2017

2016
A Stochastic Newton-Raphson Method with Noisy Function Measurements.
IEEE Signal Process. Lett., 2016

Application of an optimal stochastic Newton-Raphson technique to triangulation-based localization systems.
Proceedings of the IEEE/ION Position, Location and Navigation Symposium, 2016


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