Suchi Saria

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 52

Top Topics

Predictive Model

Measurement Error

Top Venues

IEEE Intell. Syst.

Publications

Drew Prinster, Samuel Stanton, Anqi Liu, Suchi Saria
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them). CoRR (2024)
Xing Han, Huy Nguyen, Carl Harris, Nhat Ho, Suchi Saria
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion. CoRR (2024)
H. Echo Wang, Jonathan P. Weiner, Suchi Saria, Harold P. Lehmann, Hadi Kharrazi
Assessing racial bias in healthcare predictive models: Practical lessons from an empirical evaluation of 30-day hospital readmission models. J. Biomed. Informatics 156 (2024)
Drew Prinster, Suchi Saria, Anqi Liu
JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift. ICML (2023)
Yoav Wald, Suchi Saria
Birds of an odd feather: guaranteed out-of-distribution (OOD) novel category detection. UAI (2023)
Lauren M. Sanders, Ryan T. Scott, Jason H. Yang, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart J. Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes
Biological research and self-driving labs in deep space supported by artificial intelligence. Nat. Mac. Intell. 5 (3) (2023)
Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei
Causal-structure Driven Augmentations for Text OOD Generalization. NeurIPS (2023)
Ryan T. Scott, Lauren M. Sanders, Erik L. Antonsen, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes
Biomonitoring and precision health in deep space supported by artificial intelligence. Nat. Mac. Intell. 5 (3) (2023)
Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei
Causal-structure Driven Augmentations for Text OOD Generalization. CoRR (2023)
Drew Prinster, Suchi Saria, Anqi Liu
Efficient Approximate Predictive Inference Under Feedback Covariate Shift with Influence Functions. COPA (2023)
H. Echo Wang, Matthew Landers, Roy Adams, Adarsh Subbaswamy, Hadi Kharrazi, Darrell J. Gaskin, Suchi Saria
A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models. J. Am. Medical Informatics Assoc. 29 (8) (2022)
Drew Prinster, Anqi Liu, Suchi Saria
JAWS: Auditing Predictive Uncertainty Under Covariate Shift. NeurIPS (2022)
Drew Prinster, Anqi Liu, Suchi Saria
JAWS: Predictive Inference Under Covariate Shift. CoRR (2022)
Katharine Henry, Rachel Kornfield, Anirudh Sridharan, Robert C. Linton, Catherine Groh, Tony Wang, Albert Wu, Bilge Mutlu, Suchi Saria
Human-machine teaming is key to AI adoption: clinicians' experiences with a deployed machine learning system. npj Digit. Medicine 5 (2022)
Ryan T. Scott, Erik L. Antonsen, Lauren M. Sanders, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart Chalk, Guillermo M. Delgado-Aparicio, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes
Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health. CoRR (2021)
Adarsh Subbaswamy, Roy Adams, Suchi Saria
Evaluating Model Robustness and Stability to Dataset Shift. AISTATS (2021)
Suchi Saria, Marzyeh Ghassemi, Ziad Obermeyer, Karandeep Singh, Pei-Yun S. Hsueh, Eric Topol
Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery. AMIA (2021)
Noam Finkelstein, Roy Adams, Suchi Saria, Ilya Shpitser
Partial Identifiability in Discrete Data with Measurement Error. UAI (2021)
Lauren M. Sanders, Jason H. Yang, Ryan T. Scott, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte Nelson, Jonathan Oribello, Seung-min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes
Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs. CoRR (2021)
Adarsh Subbaswamy, Suchi Saria
I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models. CoRR (2020)
Adarsh Subbaswamy, Roy Adams, Suchi Saria
Evaluating Model Robustness to Dataset Shift. CoRR (2020)
Noam Finkelstein, Roy Adams, Suchi Saria, Ilya Shpitser
Partial Identifiability in Discrete Data With Measurement Error. CoRR (2020)
Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski
Active Learning for Decision-Making from Imbalanced Observational Data. ICML (2019)
Suchi Saria, Adarsh Subbaswamy
Tutorial: Safe and Reliable Machine Learning. CoRR (2019)
Peter Schulam, Suchi Saria
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning. AISTATS (2019)
Adarsh Subbaswamy, Bryant Chen, Suchi Saria
The Hierarchy of Stable Distributions and Operators to Trade Off Stability and Performance. CoRR (2019)
Peter Schulam, Suchi Saria
Auditing Pointwise Reliability Subsequent to Training. CoRR (2019)
Roy Adams, Yuelong Ji, Xiaobin Wang, Suchi Saria
Learning Models from Data with Measurement Error: Tackling Underreporting. ICML (2019)
Roy Adams, Yuelong Ji, Xiaobin Wang, Suchi Saria
Learning Models from Data with Measurement Error: Tackling Underreporting. CoRR (2019)
Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski
Active Learning for Decision-Making from Imbalanced Observational Data. CoRR (2019)
Adarsh Subbaswamy, Peter Schulam, Suchi Saria
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport. AISTATS (2019)
Gregory D. Hager, Ann W. Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C. Parkes, Jason Schultz, Suchi Saria, Stephen F. Smith, Milind Tambe
Artificial Intelligence for Social Good. CoRR (2019)
Hossein Soleimani, James Hensman, Suchi Saria
Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 40 (8) (2018)
Adarsh Subbaswamy, Suchi Saria
Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms. UAI (2018)
Peter Schulam, Suchi Saria
Discretizing Logged Interaction Data Biases Learning for Decision-Making. CoRR (2018)
Adarsh Subbaswamy, Suchi Saria
Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms. CoRR (2018)
Adarsh Subbaswamy, Peter Schulam, Suchi Saria
Learning Predictive Models That Transport. CoRR (2018)
Hossein Soleimani, James Hensman, Suchi Saria
Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction. CoRR (2017)
Peter Schulam, Suchi Saria
What-If Reasoning with Counterfactual Gaussian Processes. CoRR (2017)
Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria
Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions. CoRR (2017)
Peter Schulam, Suchi Saria
Reliable Decision Support using Counterfactual Models. NIPS (2017)
Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria
Learning Treatment-Response Models from Multivariate Longitudinal Data. UAI (2017)
Peter Schulam, Suchi Saria
Integrative Analysis using Coupled Latent Variable Models for Individualizing Prognoses. J. Mach. Learn. Res. 17 (2016)
Kirill Dyagilev, Suchi Saria
Learning (predictive) risk scores in the presence of censoring due to interventions. Mach. Learn. 102 (3) (2016)
Austin Reiter, Andy J. Ma, Nishi Rawat, Christine Shrock, Suchi Saria
Process Monitoring in the Intensive Care Unit: Assessing Patient Mobility Through Activity Analysis with a Non-Invasive Mobility Sensor. MICCAI (1) (2016)
Daniel P. Robinson, Suchi Saria
Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models. IJCAI (2016)
Yanbo Xu, Yanxun Xu, Suchi Saria
A Bayesian Nonparametic Approach for Estimating Individualized Treatment-Response Curves. CoRR (2016)
Yanbo Xu, Yanxun Xu, Suchi Saria
A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series. MLHC (2016)
Daniel P. Robinson, Suchi Saria
Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models. CoRR (2016)
Jimeng Sun, Jim Rehg, Suchi Saria, Hua Xu, Eric P. Xing
Advanced Machine Learning for Healthcare. CRI (2016)
Andong Zhan, Max A. Little, Denzil A. Harris, Solomon O. Abiola, E. Ray Dorsey, Suchi Saria, Andreas Terzis
High Frequency Remote Monitoring of Parkinson's Disease via Smartphone: Platform Overview and Medication Response Detection. CoRR (2016)
Haris Aziz, Elias Bareinboim, Yejin Choi, Daniel J. Hsu, Shivaram Kalyanakrishnan, Reshef Meir, Suchi Saria, Gerardo I. Simari, Lirong Xia, William Yeoh
AI's 10 to Watch. IEEE Intell. Syst. 31 (1) (2016)
Andy Jinhua Ma, Pong C. Yuen, Suchi Saria
Deformable Distributed Multiple Detector Fusion for Multi-Person Tracking. CoRR (2015)
Suchi Saria, Anna Goldenberg
Subtyping: What It is and Its Role in Precision Medicine. IEEE Intell. Syst. 30 (4) (2015)
Peter Schulam, Fredrick Wigley, Suchi Saria
Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery. AAAI (2015)
Kirill Dyagilev, Suchi Saria
Learning (Predictive) Risk Scores in the Presence of Censoring due to Interventions. CoRR (2015)
Kirill Dyagilev, Suchi Saria
Learning a Severity Score for Sepsis: A Novel Approach based on Clinical Comparisons. AMIA (2015)
Peter Schulam, Suchi Saria
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure. NIPS (2015)
Peter Schulam, Colin Ligon, Robert Wise, Laura K. Hummers, Fredrick Wigley, Suchi Saria
A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases. AMIA (2015)
Suchi Saria, Gabriel J. Escobar, Paul C. Tang, Lucila Ohno-Machado, Alex Dummett
Predictive Analytics in Healthcare (HPA): Considerations and Challenges. AMIA (2014)
Suchi Saria
A $3 Trillion Challenge to Computational Scientists: Transforming Healthcare Delivery. IEEE Intell. Syst. 29 (4) (2014)
Chris Paxton, Suchi Saria, Alexandru Niculescu-Mizil
Developing Predictive Models Using Electronic Medical Records: Challenges and Pitfalls. AMIA (2013)
Suchi Saria, Uri Nodelman, Daphne Koller
Reasoning at the Right Time Granularity CoRR (2012)
Suchi Saria, Andrew Duchi, Daphne Koller
Discovering Deformable Motifs in Continuous Time Series Data. IJCAI (2011)
Vladimir Jojic, Suchi Saria, Daphne Koller
Convex envelopes of complexity controlling penalties: the case against premature envelopment. AISTATS (2011)
Suchi Saria, Daphne Koller, Anna Penn
Discovering shared and individual latent structure in multiple time series CoRR (2010)
Suchi Saria, Uri Nodelman, Daphne Koller
Reasoning at the Right Time Granularity. UAI (2007)
Hugo Zaragoza, Nick Craswell, Michael J. Taylor, Suchi Saria, Stephen E. Robertson
Microsoft Cambridge at TREC 13: Web and Hard Tracks. TREC (2004)
Suchi Saria, Sridhar Mahadevan
Probabilistic Plan Recognition in Multiagent Systems. ICAPS (2004)