Schaar, Mihaela

48 publications

AISTATS 2025 Active Feature Acquisition for Personalised Treatment Assignment Julianna Piskorz, Nicolás Astorga, Jeroen Berrevoets, Mihaela Schaar

AISTATS 2025 Beyond Size-Based Metrics: Measuring Task-Specific Complexity in Symbolic Regression Krzysztof Kacprzyk, Mihaela Schaar

AISTATS 2025 Differentiable Causal Structure Learning with Identifiability by NOTIME Jeroen Berrevoets, Jakob Raymaekers, Mihaela Schaar, Tim Verdonck, Ruicong Yao

AISTATS 2025 Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions Omer Noy Klein, Alihan Hüyük, Ron Shamir, Uri Shalit, Mihaela Schaar

AISTATS 2025 Visualizing Token Importance for Black-Box Language Models Paulius Rauba, Qiyao Wei, Mihaela Schaar

AISTATS 2024 Adaptive Experiment Design with Synthetic Controls Alihan Hüyük, Zhaozhi Qian, Mihaela Schaar

ICML 2024 Curated LLM: Synergy of LLMs and Data Curation for Tabular Augmentation in Low-Data Regimes Nabeel Seedat, Nicolas Huynh, Boris Breugel, Mihaela Schaar

AISTATS 2024 DAGnosis: Localized Identification of Data Inconsistencies Using Structures Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela Schaar

AISTATS 2024 Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations Krzysztof Kacprzyk, Mihaela Schaar

AISTATS 2023 Improving Adaptive Conformal Prediction Using Self-Supervised Learning Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela Schaar

AISTATS 2023 Membership Inference Attacks Against Synthetic Data Through Overfitting Detection Boris Breugel, Hao Sun, Zhaozhi Qian, Mihaela Schaar

AISTATS 2023 Neural Laplace Control for Continuous-Time Delayed Systems Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela Schaar

AISTATS 2023 SurvivalGAN: Generating Time-to-Event Data for Survival Analysis Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Lió, Mihaela Schaar

AISTATS 2023 T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression Yuchao Qin, Mihaela Schaar, Changhee Lee

AISTATS 2023 To Impute or Not to Impute? Missing Data in Treatment Effect Estimation Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela Schaar

AISTATS 2023 Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data Alicia Curth, Mihaela Schaar

ICML 2022 Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela Schaar

ICML 2022 Data-SUITE: Data-Centric Identification of In-Distribution Incongruous Examples Nabeel Seedat, Jonathan Crabbé, Mihaela Schaar

ICML 2022 How Faithful Is Your Synthetic Data? Sample-Level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa, Boris Van Breugel, Evgeny S. Saveliev, Mihaela Schaar

ICML 2022 HyperImpute: Generalized Iterative Imputation with Automatic Model Selection Daniel Jarrett, Bogdan C Cebere, Tennison Liu, Alicia Curth, Mihaela Schaar

ICML 2022 Inverse Contextual Bandits: Learning How Behavior Evolves over Time Alihan Hüyük, Daniel Jarrett, Mihaela Schaar

ICML 2022 Label-Free Explainability for Unsupervised Models Jonathan Crabbé, Mihaela Schaar

ICML 2022 Neural Laplace: Learning Diverse Classes of Differential Equations in the Laplace Domain Samuel I Holt, Zhaozhi Qian, Mihaela Schaar

AISTATS 2021 A Variational Information Bottleneck Approach to Multi-Omics Data Integration Changhee Lee, Mihaela Schaar

AISTATS 2021 Learning Matching Representations for Individualized Organ Transplantation Allocation Can Xu, Ahmed Alaa, Ioana Bica, Brent Ershoff, Maxime Cannesson, Mihaela Schaar

AISTATS 2021 Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms Alicia Curth, Mihaela Schaar

AISTATS 2021 SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups Hyun-Suk Lee, Cong Shen, William Zame, Jang-Won Lee, Mihaela Schaar

UAI 2021 A Kernel Two-Sample Test with Selection Bias Alexis Bellot, Mihaela Schaar

UAI 2021 Application of Kernel Hypothesis Testing on Set-Valued Data Alexis Bellot, Mihaela Schaar

ICML 2021 Learning Queueing Policies for Organ Transplantation Allocation Using Interpretable Counterfactual Survival Analysis Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela Schaar

ICML 2021 Policy Analysis Using Synthetic Controls in Continuous-Time Alexis Bellot, Mihaela Schaar

AISTATS 2020 Contextual Constrained Learning for Dose-Finding Clinical Trials Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela Schaar

AISTATS 2020 Learning Dynamic and Personalized Comorbidity Networks from Event Data Using Deep Diffusion Processes Zhaozhi Qian, Ahmed Alaa, Alexis Bellot, Mihaela Schaar, Jem Rashbass

AISTATS 2020 Learning Overlapping Representations for the Estimation of Individualized Treatment Effects Yao Zhang, Alexis Bellot, Mihaela Schaar

AISTATS 2020 Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning Yao Zhang, Daniel Jarrett, Mihaela Schaar

MLHC 2019 ASAC: Active Sensing Using Actor-Critic Models Jinsung Yoon, James Jordon, Mihaela Schaar

AISTATS 2019 Boosting Transfer Learning with Survival Data from Heterogeneous Domains Alexis Bellot, Mihaela Schaar

MLHC 2019 Multi-View Multi-Task Learning for Improving Autonomous Mammogram Diagnosis Trent Kyono, Fiona J. Gilbert, Mihaela Schaar

AISTATS 2019 Sequential Patient Recruitment and Allocation for Adaptive Clinical Trials Onur Atan, William R. Zame, Mihaela Schaar

AISTATS 2019 Temporal Quilting for Survival Analysis Changhee Lee, William Zame, Ahmed Alaa, Mihaela Schaar

ICML 2018 AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning Ahmed Alaa, Mihaela Schaar

ICML 2018 GAIN: Missing Data Imputation Using Generative Adversarial Nets Jinsung Yoon, James Jordon, Mihaela Schaar

ICML 2018 Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design Ahmed Alaa, Mihaela Schaar

ICML 2018 RadialGAN: Leveraging Multiple Datasets to Improve Target-Specific Predictive Models Using Generative Adversarial Networks Jinsung Yoon, James Jordon, Mihaela Schaar

ICML 2017 Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis Ahmed M. Alaa, Scott Hu, Mihaela Schaar

ICML 2016 Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design William Hoiles, Mihaela Schaar

ICML 2016 ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission Jinsung Yoon, Ahmed Alaa, Scott Hu, Mihaela Schaar

ICML 2015 Context-Based Unsupervised Data Fusion for Decision Making Erfan Soltanmohammadi, Mort Naraghi-Pour, Mihaela Schaar