Nabeel Seedat
Nabeel Seedat
University of Cambridge / Cornell University / University of the Witwatersrand
Verified email at - Homepage
Cited by
Cited by
Towards calibrated and scalable uncertainty representations for neural networks
N Seedat, C Kanan
NeurIPS 2019, 4th workshop on Bayesian Deep Learning, 2019
Automated stage discrimination of Parkinson’s disease
V Aharonson, N Seedat, S Israeli-Korn, S Hassin-Baer, M Postema, ...
BIO Integration 1 (2), 55-63, 2020
Custom force sensor and sensory feedback system to enable grip control of a robotic prosthetic hand
N Seedat, I Mohamed, AK Mohamed
2018 7th IEEE International Conference on Biomedical Robotics and …, 2018
Machine learning discrimination of Parkinson's Disease stages from walker-mounted sensors data
N Seedat, V Aharonson
AAAI 2020 (New York) - International Workshop on Health Intelligence, 2020
Feasibility of an instrumented walker to quantify treatment effects on Parkinson's patient gait
V Aharonson, N Seedat, I Schlesinger, A McDonald, S Dubowsky, ...
IEEE 2018 Electric Electronics, Computer Science, Biomedical Engineerings …, 2018
A comparison of footfall detection algorithms from walker mounted sensors data
N Seedat, D Beder, V Aharonson, S Dubowsky
IEEE 2018 Electric Electronics, Computer Science, Biomedical Engineerings …, 2018
Automated and interpretable m-health discrimination of vocal cord pathology enabled by machine learning
N Seedat, V Aharonson, Y Hamzany
2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering …, 2020
MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts
N Seedat
KDD 2020 - Applied Data Science in Healthcare & ICML 2020 - Uncertainty …, 2020
Automated machine vision enabled detection of movement disorders from hand drawn spirals
N Seedat, V Aharonson, I Schlesinger
2020 IEEE International Conference on Healthcare Informatics (ICHI), 2020
DAUX: a Density-based Approach for Uncertainty eXplanations
H Sun, B van Breugel, J Crabbe, N Seedat, M van der Schaar
arXiv preprint arXiv:2207.05161, 2022
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations
N Seedat, F Imrie, A Bellot, Z Qian, M van der Schaar
Proceedings of the 39th International Conference on Machine Learning, 19497 …, 2022
Differentiable and Transportable Structure Learning
J Berrevoets, N Seedat, F Imrie, M van der Schaar
arXiv preprint arXiv:2206.06354, 2022
Modeling Disagreement in Automatic Data Labelling for Semi-Supervised Learning in Clinical Natural Language Processing
H Liu*, N Seedat*, J Ive
arXiv preprint arXiv:2205.14761, 2022
Data-SUITE: Data-centric identification of in-distribution incongruous examples
N Seedat, J Crabbe, M van der Schaar
Proceedings of the 39th International Conference on Machine Learning, 19467 …, 2022
PEMS: Custom Neural Machine Translation System-Making subtitling of Portuguese TV shows and movies on the African continent work
N Seedat, N Sen, N Naicker, K Sharma, A Almeida, G Kalyansundaram, ...
2021 International Conference on Electrical, Computer and Energy …, 2021
Latent Density Models for Uncertainty Categorization
H Sun, B van Breugel, J Crabbé, N Seedat, M van der Schaar
Quadcopter Control using Intelligent Control Methods
N Seedat, A Van Wyk
Deep Learning Indaba 2017, 0
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Articles 1–17