Andrew C. Miller

33 papers A* 7A 1Journal 20Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Anti-causal domain generalization: Leveraging unlabeled data. CoRR Sorawit Saengkyongam, Juan L. Gamella, Andrew C. Miller, Jonas Peters, Nicolai Meinshausen, Christina Heinze-Deml
2025	A*	`conf`	Do LLMs "know" internally when they follow instructions? ICLR Juyeon Heo, Christina Heinze-Deml, Oussama Elachqar, Kwan Ho Ryan Chan, Shirley You Ren, Andrew C. Miller, Udhyakumar Nallasamy, Jaya Narain
2025	J	`jnl`	Hybrid Modeling of Photoplethysmography for Non-invasive Monitoring of Cardiovascular Parameters. CoRR Emanuele Palumbo, Sorawit Saengkyongam, Maria R. Cervera, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Christina Heinze-Deml, Antoine Wehenkel
2025	J	`jnl`	Inferring Optical Tissue Properties from Photoplethysmography using Hybrid Amortized Inference. CoRR Jens Behrmann, Maria R. Cervera, Antoine Wehenkel, Andrew C. Miller, Albert Cerussi, Pranay Jain, Vivek Venugopal, Shijie Yan, Guillermo Sapiro, Luca Pegolotti, Jörn-Henrik Jacobsen
2025	J	`jnl`	Wrist Photoplethysmography Predicts Dietary Information. CoRR Kyle Verrier, Achille Nazaret, Joseph Futoma, Andrew C. Miller, Guillermo Sapiro
2024	J	`jnl`	Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare. CoRR Arno Blaas, Adam Golinski, Andrew C. Miller, Luca Zappella, Jörn-Henrik Jacobsen, Christina Heinze-Deml
2024	A*	`conf`	Large-scale Training of Foundation Models for Wearable Biosignals. ICLR Salar Abbaspourazad, Oussama Elachqar, Andrew C. Miller, Saba Emrani, Udhyakumar Nallasamy, Ian Shapiro
2024	J	`jnl`	Wearable Accelerometer Foundation Models for Health via Knowledge Distillation. CoRR Salar Abbaspourazad, Anshuman Mishra, Joseph Futoma, Andrew C. Miller, Ian Shapiro
2023	J	`jnl`	Large-scale Training of Foundation Models for Wearable Biosignals. CoRR Salar Abbaspourazad, Oussama Elachqar, Andrew C. Miller, Saba Emrani, Udhyakumar Nallasamy, Ian Shapiro
2023	J	`jnl`	Modeling personalized heart rate response to exercise and environmental factors with wearables data. npj Digit. Medicine Achille Nazaret, Sana Tonekaboni, Gregory Darnell, Shirley You Ren, Guillermo Sapiro, Andrew C. Miller
2023	J	`jnl`	Simulation-based Inference for Cardiovascular Models. CoRR Antoine Wehenkel, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Ozan Sener, Marco Cuturi, Jörn-Henrik Jacobsen
2022	—	`conf`	Learning Invariant Representations with Missing Data. CLeaR Mark Goldstein, Jörn-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Manas Puli, Rajesh Ranganath, Andrew C. Miller
2021	J	`jnl`	Breiman's two cultures: You don't have to choose sides. CoRR Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
2021	J	`jnl`	It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US. npj Digit. Medicine Sean Jewell, Joseph Futoma, Lauren Hannah, Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
2021	J	`jnl`	Learning Invariant Representations with Missing Data. CoRR Mark Goldstein, Jörn-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Manas Puli, Rajesh Ranganath, Andrew C. Miller
2021	—	`conf`	Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. MLHC Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox
2021	J	`jnl`	Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. CoRR Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox
2020	—	`conf`	Learning Insulin-Glucose Dynamics in the Wild. MLHC Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
2020	J	`jnl`	Learning Insulin-Glucose Dynamics in the Wild. CoRR Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
2020	J	`jnl`	Representing and Denoising Wearable ECG Recordings. CoRR Jeffrey Chan, Andrew C. Miller, Emily B. Fox
2019	A*	`conf`	Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography. ICML Andrew C. Miller, Ziad Obermeyer, John P. Cunningham, Sendhil Mullainathan
2018	J	`jnl`	A Probabilistic Model of Cardiac Physiology and Electrocardiograms. CoRR Andrew C. Miller, Ziad Obermeyer, David M. Blei, John P. Cunningham, Sendhil Mullainathan
2018	J	`jnl`	Approximate Inference for Constructing Astronomical Catalogs from Images. CoRR Jeffrey Regier, Andrew C. Miller, David Schlegel, Ryan P. Adams, Jon D. McAuliffe, Prabhat
2018	J	`jnl`	Measuring the Stability of EHR- and EKG-based Predictive Models. CoRR Andrew C. Miller, Ziad Obermeyer, Sendhil Mullainathan
2018	A*	`conf`	Semi-Amortized Variational Autoencoders. ICML Yoon Kim, Sam Wiseman, Andrew C. Miller, David A. Sontag, Alexander M. Rush
2018	J	`jnl`	Semi-Amortized Variational Autoencoders. CoRR Yoon Kim, Sam Wiseman, Andrew C. Miller, David A. Sontag, Alexander M. Rush
2017	A	`conf`	Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems. AISTATS Scott W. Linderman, Matthew J. Johnson, Andrew C. Miller, Ryan P. Adams, David M. Blei, Liam Paninski
2017	—	`conf`	Reducing Reparameterization Gradient Variance. NIPS Andrew C. Miller, Nick Foti, Alexander D'Amour, Ryan P. Adams
2017	A*	`conf`	Variational Boosting: Iteratively Refining Posterior Approximations. ICML Andrew C. Miller, Nicholas J. Foti, Ryan P. Adams
2016	J	`jnl`	Variational Boosting: Iteratively Refining Posterior Approximations. CoRR Andrew C. Miller, Nicholas J. Foti, Ryan P. Adams
2015	—	`conf`	A Gaussian Process Model of Quasar Spectral Energy Distributions. NIPS Andrew C. Miller, Albert Wu, Jeffrey Regier, Jon McAuliffe, Dustin Lang, Prabhat, David Schlegel, Ryan P. Adams
2015	A*	`conf`	Celeste: Variational inference for a generative model of astronomical images. ICML Jeffrey Regier, Andrew C. Miller, Jon McAuliffe, Ryan P. Adams, Matthew D. Hoffman, Dustin Lang, David Schlegel, Prabhat
2014	A*	`conf`	Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball. ICML Andrew C. Miller, Luke Bornn, Ryan P. Adams, Kirk Goldsberry