Aniruddh Raghu
Aniruddh Raghu
Verified email at
Cited by
Cited by
Rapid learning or feature reuse? towards understanding the effectiveness of maml
A Raghu, M Raghu, S Bengio, O Vinyals
arXiv preprint arXiv:1909.09157, 2019
Continuous state-space models for optimal sepsis treatment: a deep reinforcement learning approach
A Raghu, M Komorowski, LA Celi, P Szolovits, M Ghassemi
Machine Learning for Healthcare Conference, 147-163, 2017
Deep reinforcement learning for sepsis treatment
A Raghu, M Komorowski, I Ahmed, L Celi, P Szolovits, M Ghassemi
arXiv preprint arXiv:1711.09602, 2017
Through-wall human mesh recovery using radio signals
M Zhao, Y Liu, A Raghu, T Li, H Zhao, A Torralba, D Katabi
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Representation balancing mdps for off-policy policy evaluation
Y Liu, O Gottesman, A Raghu, M Komorowski, AA Faisal, F Doshi-Velez, ...
Advances in neural information processing systems 31, 2018
Assessment of medication self-administration using artificial intelligence
M Zhao, K Hoti, H Wang, A Raghu, D Katabi
Nature medicine 27 (4), 727-735, 2021
Model-based reinforcement learning for sepsis treatment
A Raghu, M Komorowski, S Singh
arXiv preprint arXiv:1811.09602, 2018
Behaviour policy estimation in off-policy policy evaluation: Calibration matters
A Raghu, O Gottesman, Y Liu, M Komorowski, A Faisal, F Doshi-Velez, ...
arXiv preprint arXiv:1807.01066, 2018
Meta-learning to improve pre-training
A Raghu, J Lorraine, S Kornblith, M McDermott, DK Duvenaud
Advances in Neural Information Processing Systems 34, 23231-23244, 2021
Detecting surface flaws using computer vision
A Raghu, J Rutland, C Leistner, AP Torres
US Patent 10,346,969, 2019
Teaching with commentaries
A Raghu, M Raghu, S Kornblith, D Duvenaud, G Hinton
arXiv preprint arXiv:2011.03037, 2020
Data augmentation for electrocardiograms
A Raghu, D Shanmugam, E Pomerantsev, J Guttag, CM Stultz
Conference on Health, Inference, and Learning, 282-310, 2022
A deep learning model for inferring elevated pulmonary capillary wedge pressures from the 12-lead electrocardiogram
DE Schlesinger, N Diamant, A Raghu, E Reinertsen, K Young, P Batra, ...
JACC: Advances 1 (1), 100003, 2022
Sequential multi-dimensional self-supervised learning for clinical time series
A Raghu, P Chandak, R Alam, J Guttag, C Stultz
International Conference on Machine Learning, 28531-28548, 2023
ECG-guided non-invasive estimation of pulmonary congestion in patients with heart failure
A Raghu, D Schlesinger, E Pomerantsev, S Devireddy, P Shah, J Garasic, ...
Scientific Reports 13 (1), 3923, 2023
Learning to predict with supporting evidence: Applications to clinical risk prediction
A Raghu, J Guttag, K Young, E Pomerantsev, AV Dalca, CM Stultz
Proceedings of the Conference on Health, Inference, and Learning, 95-104, 2021
Reinforcement learning for sepsis treatment: Baselines and analysis
A Raghu
Generative Humanization for Therapeutic Antibodies
CW Gordon, A Raghu, P Greenside, H Elliott
ICLR 2024 Workshop on Generative and Experimental Perspectives for …, 2024
Data-Efficient Machine Learning with Applications to Cardiology
A Raghu
Massachusetts Institute of Technology, 2024
The system can't perform the operation now. Try again later.
Articles 1–19