Khaled Kamal Saab
Khaled Kamal Saab
Google, Stanford University
Verified email at - Homepage
Cited by
Cited by
Combining recurrent, convolutional, and continuous-time models with linear state space layers
A Gu, I Johnson, K Goel, K Saab, T Dao, A Rudra, C Ré
Advances in neural information processing systems 34, 572-585, 2021
Hungry hungry hippos: Towards language modeling with state space models
DY Fu, T Dao, KK Saab, AW Thomas, A Rudra, C Ré
arXiv preprint arXiv:2212.14052, 2022
Protecting bare-metal embedded systems with privilege overlays
AA Clements, NS Almakhdhub, KS Saab, P Srivastava, J Koo, S Bagchi, ...
2017 IEEE Symposium on Security and Privacy (SP), 289-303, 2017
Domino: Discovering systematic errors with cross-modal embeddings
S Eyuboglu, M Varma, K Saab, JB Delbrouck, C Lee-Messer, J Dunnmon, ...
arXiv preprint arXiv:2203.14960, 2022
Self-supervised graph neural networks for improved electroencephalographic seizure analysis
S Tang, JA Dunnmon, K Saab, X Zhang, Q Huang, F Dubost, DL Rubin, ...
arXiv preprint arXiv:2104.08336, 2021
Weak supervision as an efficient approach for automated seizure detection in electroencephalography
K Saab, J Dunnmon, C Ré, D Rubin, C Lee-Messer
NPJ digital medicine 3 (1), 59, 2020
Cross-modal data programming enables rapid medical machine learning
JA Dunnmon, AJ Ratner, K Saab, N Khandwala, M Markert, H Sagreiya, ...
Patterns 1 (2), 2020
Towards conversational diagnostic ai
T Tu, A Palepu, M Schaekermann, K Saab, J Freyberg, R Tanno, A Wang, ...
arXiv preprint arXiv:2401.05654, 2024
Effectively modeling time series with simple discrete state spaces
M Zhang, KK Saab, M Poli, T Dao, K Goel, C Ré
arXiv preprint arXiv:2303.09489, 2023
Observational supervision for medical image classification using gaze data
K Saab, SM Hooper, NS Sohoni, J Parmar, B Pogatchnik, S Wu, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
Doubly weak supervision of deep learning models for head CT
K Saab, J Dunnmon, R Goldman, A Ratner, H Sagreiya, C Ré, D Rubin
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
A multivariate adaptive gradient algorithm with reduced tuning efforts
S Saab Jr, K Saab, S Phoha, M Zhu, A Ray
Neural Networks 152, 499-509, 2022
Capabilities of gemini models in medicine
K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ...
arXiv preprint arXiv:2404.18416, 2024
ViLMedic: a framework for research at the intersection of vision and language in medical AI
J Delbrouck, K Saab, M Varma, S Eyuboglu, P Chambon, J Dunnmon, ...
Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022
Setting the boundaries of COVID-19 lockdown relaxation measures
S Saab, M Al Abbas, RN Samaha, R Jaafar, KK Saab, SS Saab Jr
Library Hi Tech 39 (3), 873-887, 2021
Modeling multivariate biosignals with graph neural networks and structured state space models
S Tang, JA Dunnmon, Q Liangqiong, KK Saab, T Baykaner, ...
Conference on Health, Inference, and Learning, 50-71, 2023
Shuffled linear regression with erroneous observations
SS Saab, KK Saab
2019 53rd annual conference on information sciences and systems (CISS), 1-6, 2019
A positioning system for photodiode device using collocated LEDs
SS Saab, KK Saab
IEEE Photonics Journal 8 (5), 1-14, 2016
A stochastic Newton-Raphson method with noisy function measurements
KK Saab, SS Saab
IEEE signal processing letters 23 (3), 361-365, 2015
Application of an optimal stochastic Newton-Raphson technique to triangulation-based localization systems
KK Saab, SS Saab
2016 IEEE/ION Position, Location and Navigation Symposium (PLANS), 981-986, 2016
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