Suchi Saria

Orcid: 0000-0002-7667-5210

Affiliations:
  • Johns Hopkins University, Baltimore, MD, USA


According to our database1, Suchi Saria authored at least 63 papers between 2004 and 2024.

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Bibliography

2024
Assessing racial bias in healthcare predictive models: Practical lessons from an empirical evaluation of 30-day hospital readmission models.
J. Biomed. Informatics, 2024

On Expert Estimation in Hierarchical Mixture of Experts: Beyond Softmax Gating Functions.
CoRR, 2024

FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion.
CoRR, 2024

Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them).
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Biomonitoring and precision health in deep space supported by artificial intelligence.
Nat. Mac. Intell., March, 2023

Biological research and self-driving labs in deep space supported by artificial intelligence.
Nat. Mac. Intell., March, 2023

Birds of an odd feather: guaranteed out-of-distribution (OOD) novel category detection.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Causal-structure Driven Augmentations for Text OOD Generalization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift.
Proceedings of the International Conference on Machine Learning, 2023

Efficient Approximate Predictive Inference Under Feedback Covariate Shift with Influence Functions.
Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

2022
Human-machine teaming is key to AI adoption: clinicians' experiences with a deployed machine learning system.
npj Digit. Medicine, 2022

A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models.
J. Am. Medical Informatics Assoc., 2022

JAWS: Predictive Inference Under Covariate Shift.
CoRR, 2022

JAWS: Auditing Predictive Uncertainty Under Covariate Shift.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs.
CoRR, 2021

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health.
CoRR, 2021

Partial Identifiability in Discrete Data with Measurement Error.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Evaluating Model Robustness and Stability to Dataset Shift.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Evaluating Model Robustness to Dataset Shift.
CoRR, 2020

I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models.
CoRR, 2020

2019
The Hierarchy of Stable Distributions and Operators to Trade Off Stability and Performance.
CoRR, 2019

Tutorial: Safe and Reliable Machine Learning.
CoRR, 2019

Artificial Intelligence for Social Good.
CoRR, 2019

Auditing Pointwise Reliability Subsequent to Training.
CoRR, 2019

Active Learning for Decision-Making from Imbalanced Observational Data.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Models from Data with Measurement Error: Tackling Underreporting.
Proceedings of the 36th International Conference on Machine Learning, 2019

Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Can You Trust This Prediction? Auditing Pointwise Reliability After Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Learning Predictive Models That Transport.
CoRR, 2018

Discretizing Logged Interaction Data Biases Learning for Decision-Making.
CoRR, 2018

Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms.
CoRR, 2018

Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

2017
Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions.
CoRR, 2017

What-If Reasoning with Counterfactual Gaussian Processes.
CoRR, 2017

Learning Treatment-Response Models from Multivariate Longitudinal Data.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Reliable Decision Support using Counterfactual Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Learning (predictive) risk scores in the presence of censoring due to interventions.
Mach. Learn., 2016

Integrative Analysis using Coupled Latent Variable Models for Individualizing Prognoses.
J. Mach. Learn. Res., 2016

AI's 10 to Watch.
IEEE Intell. Syst., 2016

High Frequency Remote Monitoring of Parkinson's Disease via Smartphone: Platform Overview and Medication Response Detection.
CoRR, 2016

A Bayesian Nonparametic Approach for Estimating Individualized Treatment-Response Curves.
CoRR, 2016

A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series.
Proceedings of the 1st Machine Learning in Health Care, 2016

Process Monitoring in the Intensive Care Unit: Assessing Patient Mobility Through Activity Analysis with a Non-Invasive Mobility Sensor.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Advanced Machine Learning for Healthcare.
Proceedings of the Summit on Clinical Research Informatics, 2016

2015
Subtyping: What It is and Its Role in Precision Medicine.
IEEE Intell. Syst., 2015

Deformable Distributed Multiple Detector Fusion for Multi-Person Tracking.
CoRR, 2015

A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases.
Proceedings of the AMIA 2015, 2015

Learning a Severity Score for Sepsis: A Novel Approach based on Clinical Comparisons.
Proceedings of the AMIA 2015, 2015

Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
A $3 Trillion Challenge to Computational Scientists: Transforming Healthcare Delivery.
IEEE Intell. Syst., 2014

Predictive Analytics in Healthcare (HPA): Considerations and Challenges.
Proceedings of the AMIA 2014, 2014

2013
Developing Predictive Models Using Electronic Medical Records: Challenges and Pitfalls.
Proceedings of the AMIA 2013, 2013

2011
The digital patient: machine learning techniques for analyzing electronic health record data.
PhD thesis, 2011

Convex envelopes of complexity controlling penalties: the case against premature envelopment.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Discovering Deformable Motifs in Continuous Time Series Data.
Proceedings of the IJCAI 2011, 2011

2010
Discovering shared and individual latent structure in multiple time series
CoRR, 2010

2007
Reasoning at the Right Time Granularity.
Proceedings of the UAI 2007, 2007

2004
Microsoft Cambridge at TREC 13: Web and Hard Tracks.
Proceedings of the Thirteenth Text REtrieval Conference, 2004

Probabilistic Plan Recognition in Multiagent Systems.
Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling (ICAPS 2004), 2004


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