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Aniruddh Raghu
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2020 – today
- 2024
- [b1]Aniruddh Raghu:
Data-Efficient Machine Learning with Applications to Cardiology. MIT, USA, 2024 - 2023
- [c9]Aniruddh Raghu, Payal Chandak, Ridwan Alam, John V. Guttag, Collin M. Stultz:
Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series. ICML 2023: 28531-28548 - [i11]Aniruddh Raghu, Payal Chandak, Ridwan Alam, John V. Guttag, Collin M. Stultz:
Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series. CoRR abs/2307.10923 (2023) - 2022
- [c8]Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz:
Data Augmentation for Electrocardiograms. CHIL 2022: 282-310 - [i10]Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz:
Data Augmentation for Electrocardiograms. CoRR abs/2204.04360 (2022) - 2021
- [c7]Aniruddh Raghu, John V. Guttag
, Katherine Young
, Eugene Pomerantsev, Adrian V. Dalca, Collin M. Stultz:
Learning to predict with supporting evidence: applications to clinical risk prediction. CHIL 2021: 95-104 - [c6]Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton:
Teaching with Commentaries. ICLR 2021 - [c5]Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud:
Meta-learning to Improve Pre-training. NeurIPS 2021: 23231-23244 - [i9]Aniruddh Raghu, John V. Guttag, Katherine Young, Eugene Pomerantsev, Adrian V. Dalca, Collin M. Stultz:
Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction. CoRR abs/2103.02768 (2021) - [i8]Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud:
Meta-Learning to Improve Pre-Training. CoRR abs/2111.01754 (2021) - 2020
- [c4]Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals:
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML. ICLR 2020 - [i7]Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton:
Teaching with Commentaries. CoRR abs/2011.03037 (2020)
2010 – 2019
- 2019
- [c3]Mingmin Zhao, Yingcheng Liu, Aniruddh Raghu, Hang Zhao, Tianhong Li, Antonio Torralba, Dina Katabi:
Through-Wall Human Mesh Recovery Using Radio Signals. ICCV 2019: 10112-10121 - [i6]Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals:
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML. CoRR abs/1909.09157 (2019) - 2018
- [c2]Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A. Faisal, Finale Doshi-Velez, Emma Brunskill:
Representation Balancing MDPs for Off-policy Policy Evaluation. NeurIPS 2018: 2649-2658 - [i5]Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill:
Representation Balancing MDPs for Off-Policy Policy Evaluation. CoRR abs/1805.09044 (2018) - [i4]Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill:
Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. CoRR abs/1807.01066 (2018) - [i3]Aniruddh Raghu, Matthieu Komorowski, Sumeetpal S. Singh:
Model-Based Reinforcement Learning for Sepsis Treatment. CoRR abs/1811.09602 (2018) - 2017
- [c1]Aniruddh Raghu, Matthieu Komorowski, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi:
Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach. MLHC 2017: 147-163 - [i2]Aniruddh Raghu, Matthieu Komorowski, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi:
Continuous State-Space Models for Optimal Sepsis Treatment - a Deep Reinforcement Learning Approach. CoRR abs/1705.08422 (2017) - [i1]Aniruddh Raghu, Matthieu Komorowski, Imran Ahmed, Leo A. Celi, Peter Szolovits, Marzyeh Ghassemi:
Deep Reinforcement Learning for Sepsis Treatment. CoRR abs/1711.09602 (2017)
Coauthor Index
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