Artur Dubrawski
Artur Dubrawski
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Cited by
Cited by
HPC strength prediction using artificial neural network
J Kasperkiewicz, J Racz, A Dubrawski
Journal of Computing in Civil Engineering 9 (4), 279-284, 1995
Nhits: Neural hierarchical interpolation for time series forecasting
C Challu, KG Olivares, BN Oreshkin, FG Ramirez, MM Canseco, ...
Proceedings of the AAAI conference on artificial intelligence 37 (6), 6989-6997, 2023
Robot learning in homes: Improving generalization and reducing dataset bias
A Gupta, A Murali, DP Gandhi, L Pinto
Advances in neural information processing systems 31, 2018
36th international symposium on intensive care and emergency medicine: Brussels, Belgium. 15-18 March 2016
RM Bateman, MD Sharpe, JE Jagger, CG Ellis, J Solé-Violán, ...
Critical care 20, 13-182, 2016
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data With Competing Risks
C Nagpal, X Li, A Dubrawski
IEEE Journal of Biomedical and Health Informatics 25 (8), 3163-3175, 2021
Leveraging publicly available data to discern patterns of human-trafficking activity
A Dubrawski, K Miller, M Barnes, B Boecking, E Kennedy
Journal of Human Trafficking 1 (1), 65-85, 2015
Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
KG Olivares, C Challu, G Marcjasz, R Weron, A Dubrawski
International Journal of Forecasting 39 (2), 884-900, 2023
A call to alarms: current state and future directions in the battle against alarm fatigue
M Hravnak, T Pellathy, L Chen, A Dubrawski, A Wertz, G Clermont, ...
Journal of electrocardiology 51 (6), S44-S48, 2018
Using supervised machine learning to classify real alerts and artifact in online multisignal vital sign monitoring data
L Chen, A Dubrawski, D Wang, M Fiterau, M Guillame-Bert, E Bose, ...
Critical care medicine 44 (7), e456-e463, 2016
Interactive weak supervision: Learning useful heuristics for data labeling
B Boecking, W Neiswanger, E Xing, A Dubrawski
arXiv preprint arXiv:2012.06046, 2020
Machine learning for the developing world
M De-Arteaga, W Herlands, DB Neill, A Dubrawski
ACM Transactions on Management Information Systems (TMIS) 9 (2), 1-14, 2018
Gleaning knowledge from data in the intensive care unit
MR Pinsky, A Dubrawski
American journal of respiratory and critical care medicine 190 (6), 606-610, 2014
Active learning for graph neural networks via node feature propagation
Y Wu, Y Xu, A Singh, Y Yang, A Dubrawski
arXiv preprint arXiv:1910.07567, 2019
Whole-genome sequencing surveillance and machine learning of the electronic health record for enhanced healthcare outbreak detection
AJ Sundermann, J Chen, P Kumar, AM Ayres, ST Cho, C Ezeonwuka, ...
Clinical Infectious Diseases 75 (3), 476-482, 2022
Learning locomotion reflexes: A self-supervised neural system for a mobile robot
A Dubrawski, JL Crowley
Robotics and Autonomous Systems 12 (3-4), 133-142, 1994
Preference-based reinforcement learning with finite-time guarantees
Y Xu, R Wang, L Yang, A Singh, A Dubrawski
Advances in Neural Information Processing Systems 33, 18784-18794, 2020
Detection of radioactive sources in urban scenes using Bayesian Aggregation of data from mobile spectrometers
P Tandon, P Huggins, R Maclachlan, A Dubrawski, K Nelson, S Labov
Information Systems 57, 195-206, 2016
Dynamic and personalized risk forecast in step-down units. Implications for monitoring paradigms
L Chen, O Ogundele, G Clermont, M Hravnak, MR Pinsky, AW Dubrawski
Annals of the American Thoracic Society 14 (3), 384-391, 2017
An entity resolution approach to isolate instances of human trafficking online
C Nagpal, K Miller, B Boecking, A Dubrawski
arXiv preprint arXiv:1509.06659, 2015
End-to-end weak supervision
S Rühling Cachay, B Boecking, A Dubrawski
Advances in Neural Information Processing Systems 34, 1845-1857, 2021
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