1. Data Augmentation for Electrocardiograms Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John Guttag, Collin M Stultz In Conference on Health, Inference, and Learning 2022 [link]
  2. A deep learning model for inferring elevated pulmonary capillary wedge pressures from the 12-lead electrocardiogram Daphne E Schlesinger, Nathaniel Diamant, Aniruddh Raghu, Erik Reinertsen, Katherine Young, Puneet Batra, Eugene Pomerantsev, Collin M Stultz JACC: Advances 2022 [link]
  3. Meta-learning to Improve Pre-training Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David K Duvenaud In Neural Information Processing Systems 2021 [link]
  4. Teaching with Commentaries Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey Hinton In International Conference on Learning Representations 2021 [link]
  5. Learning to predict with supporting evidence: Applications to clinical risk prediction Aniruddh Raghu, John Guttag, Katherine Young, Eugene Pomerantsev, Adrian V Dalca, Collin M Stultz In Proceedings of the Conference on Health, Inference, and Learning 2021 [link]
  6. Assessment of medication self-administration using artificial intelligence Mingmin Zhao, Kreshnik Hoti, Hao Wang, Aniruddh Raghu, Dina Katabi Nature Medicine 2021 [link]
  7. Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals In International Conference on Learning Representations 2020 [link]
  8. Through-Wall Human Mesh Recovery Using Radio Signals Mingmin Zhao, Yingcheng Liu, Aniruddh Raghu, Tianhong Li, Hang Zhao, Antonio Torralba, Dina Katabi In International Conference on Computer Vision 2019 [link]
  9. Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill International Conference on Machine Learning: workshop on Causal Machine Learning 2018 [link]
  10. Representation Balancing MDPs for Off-Policy Policy Evaluation Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A Faisal, Finale Doshi-Velez, Emma Brunskill In Neural Information Processing Systems 2018 [link]
  11. Model-Based Reinforcement Learning for Sepsis Treatment Aniruddh Raghu, Matthieu Komorowski, Sumeetpal Singh Neural Information Processing Systems: workshop on Machine Learning for Health 2018 [link]
  12. Masters Thesis: Reinforcement Learning for Clinical Decision Support Aniruddh Raghu 2018 [link]
  13. Deep Reinforcement Learning for Sepsis Treatment Aniruddh Raghu, Matthieu Komorowski, Imran Ahmed, Leo A. Celi, Peter Szolovits, Marzyeh Ghassemi Neural Information Processing Systems: workshop on Machine Learning for Health 2017 [link]
  14. Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach Aniruddh Raghu, Matthieu Komorowski, Leo A. Celi, Peter Szolovits, Marzyeh Ghassemi In Machine Learning for Healthcare Conference 2017 [link]