Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach. - Aniruddh Raghu; Matthieu Komorowski; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2017)

Deep Reinforcement Learning for Sepsis Treatment. - Aniruddh Raghu; Matthieu Komorowski; Imran Ahmed; Leo A. Celi; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2017)

Representation Balancing MDPs for Off-policy Policy Evaluation. - Yao Liu 009; Omer Gottesman; Aniruddh Raghu; Matthieu Komorowski; Aldo A. Faisal; Finale Doshi-Velez; Emma Brunskill (NeurIPS, 2018)

Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. - Aniruddh Raghu; Omer Gottesman; Yao Liu 009; Matthieu Komorowski; Aldo Faisal; Finale Doshi-Velez; Emma Brunskill (CoRR, 2018)

Model-Based Reinforcement Learning for Sepsis Treatment. - Aniruddh Raghu; Matthieu Komorowski; Sumeetpal S. Singh (CoRR, 2018)

Through-Wall Human Mesh Recovery Using Radio Signals. - Mingmin Zhao; Yingcheng Liu; Aniruddh Raghu; Hang Zhao; Tianhong Li; Antonio Torralba 001; Dina Katabi (ICCV, 2019)

Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML. - Aniruddh Raghu; Maithra Raghu; Samy Bengio; Oriol Vinyals (ICLR, 2020)

Learning to predict with supporting evidence: applications to clinical risk prediction. - Aniruddh Raghu; John V. Guttag; Katherine Young; Eugene Pomerantsev; Adrian V. Dalca; Collin M. Stultz (CHIL, 2021)

Teaching with Commentaries. - Aniruddh Raghu; Maithra Raghu; Simon Kornblith; David Duvenaud; Geoffrey E. Hinton (ICLR, 2021)

Meta-learning to Improve Pre-training. - Aniruddh Raghu; Jonathan Lorraine; Simon Kornblith; Matthew McDermott; David Duvenaud (NeurIPS, 2021)

Data Augmentation for Electrocardiograms. - Aniruddh Raghu; Divya Shanmugam; Eugene Pomerantsev; John V. Guttag; Collin M. Stultz (CHIL, 2022)

Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series. - Aniruddh Raghu; Payal Chandak; Ridwan Alam; John V. Guttag; Collin M. Stultz (ICML, 2023)

Generative Humanization for Therapeutic Antibodies. - Cade Gordon; Aniruddh Raghu; Peyton Greenside; Hunter Elliott (CoRR, 2024)

Data-Efficient Machine Learning with Applications to Cardiology - Aniruddh Raghu (2024)

Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences. - Alan Nawzad Amin; Nate Gruver; Yilun Kuang; Yucen Lily Li; Hunter Elliott; Calvin McCarter; Aniruddh Raghu; Peyton Greenside; Andrew Gordon Wilson (ICLR, 2025)