Mihaela van der Schaar

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 436

Top Venues

Publications

Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar
A Neural Framework for Generalized Causal Sensitivity Analysis. ICLR (2024)
Krzysztof Kacprzyk, Mihaela van der Schaar
Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations. AISTATS (2024)
Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar
Adaptive Experiment Design with Synthetic Controls. CoRR (2024)
Boris van Breugel, Mihaela van der Schaar
Why Tabular Foundation Models Should Be a Research Priority. CoRR (2024)
Yangming Li, Mihaela van der Schaar
On Error Propagation of Diffusion Models. ICLR (2024)
Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar
Adaptive Experiment Design with Synthetic Controls. AISTATS (2024)
Yangming Li, Boris van Breugel, Mihaela van der Schaar
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models. ICLR (2024)
Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar
Towards Transparent Time Series Forecasting. ICLR (2024)
Hao Sun, Mihaela van der Schaar
Inverse-RLignment: Inverse Reinforcement Learning from Demonstrations for LLM Alignment. CoRR (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI. ICLR (2024)
Boris van Breugel, Jonathan Crabbé, Rob Davis, Mihaela van der Schaar
LaTable: Towards Large Tabular Models. CoRR (2024)
Samuel Holt, Max Ruiz Luyten, Mihaela van der Schaar
L2MAC: Large Language Model Automatic Computer for Extensive Code Generation. ICLR (2024)
Lea Goetz, Nabeel Seedat, Robert Vandersluis, Mihaela van der Schaar
Generalization - a key challenge for responsible AI in patient-facing clinical applications. npj Digit. Medicine 7 (1) (2024)
Jonathan Crabbé, Nicolas Huynh, Jan Stanczuk, Mihaela van der Schaar
Time Series Diffusion in the Frequency Domain. CoRR (2024)
Jeroen Berrevoets, Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar
Causal Deep Learning: Encouraging Impact on Real-world Problems Through Causality. Found. Trends Signal Process. 18 (3) (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI. CoRR (2024)
Alicia Curth, Alan Jeffares, Mihaela van der Schaar
Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers. CoRR (2024)
Katarzyna Kobalczyk, Mihaela van der Schaar
Informed Meta-Learning. CoRR (2024)
Thomas Pouplin, Alan Jeffares, Nabeel Seedat, Mihaela van der Schaar
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise. CoRR (2024)
Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar
Large Language Models to Enhance Bayesian Optimization. CoRR (2024)
Jonas Schweisthal, Dennis Frauen, Mihaela van der Schaar, Stefan Feuerriegel
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments. CoRR (2024)
Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar
Deep Generative Symbolic Regression. CoRR (2024)
Nabeel Seedat, Nicolas Huynh, Fergus Imrie, Mihaela van der Schaar
You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling. CoRR (2024)
Alihan Hüyük, Qiyao Wei, Alicia Curth, Mihaela van der Schaar
Defining Expertise: Applications to Treatment Effect Estimation. ICLR (2024)
Hao Sun, Alihan Hüyük, Mihaela van der Schaar
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL. ICLR (2024)
Alihan Hüyük, Qiyao Wei, Alicia Curth, Mihaela van der Schaar
Defining Expertise: Applications to Treatment Effect Estimation. CoRR (2024)
Thomas Pouplin, Hao Sun, Samuel Holt, Mihaela van der Schaar
Retrieval-Augmented Thought Process as Sequential Decision Making. CoRR (2024)
Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference. ICLR (2024)
Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar
Large Language Models to Enhance Bayesian Optimization. ICLR (2024)
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
DAGnosis: Localized Identification of Data Inconsistencies using Structures. AISTATS (2024)
Alex J. Chan, Hao Sun, Samuel Holt, Mihaela van der Schaar
Dense Reward for Free in Reinforcement Learning from Human Feedback. CoRR (2024)
Alexis Bellot, Mihaela van der Schaar
Linear Deconfounded Score Method: Scoring DAGs With Dense Unobserved Confounding. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Yangming Li, Mihaela van der Schaar
A Study of Posterior Stability for Time-Series Latent Diffusion. CoRR (2024)
Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse, Dries Testelmans, Mihaela van der Schaar, Maarten De Vos
U-PASS: An uncertainty-guided deep learning pipeline for automated sleep staging. Comput. Biol. Medicine 171 (2024)
Yangming Li, Max Ruiz Luyten, Mihaela van der Schaar
Risk-Sensitive Diffusion: Learning the Underlying Distribution from Noisy Samples. CoRR (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Navigating Data-Centric Artificial Intelligence With DC-Check: Advances, Challenges, and Opportunities. IEEE Trans. Artif. Intell. 5 (6) (2024)
Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference. CoRR (2024)
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
DAGnosis: Localized Identification of Data Inconsistencies using Structures. CoRR (2024)
Chris Lu, Samuel Holt, Claudio Fanconi, Alex J. Chan, Jakob N. Foerster, Mihaela van der Schaar, Robert Tjarko Lange
Discovering Preference Optimization Algorithms with and for Large Language Models. CoRR (2024)
Krzysztof Kacprzyk, Mihaela van der Schaar
Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations. CoRR (2024)
Fergus Imrie, Stefan Denner, Lucas S. Brunschwig, Klaus H. Maier-Hein, Mihaela van der Schaar
Automated Ensemble Multimodal Machine Learning for Healthcare. CoRR (2024)
Jeroen Berrevoets, Daniel Jarrett, Alex J. Chan, Mihaela van der Schaar
AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems. NeurIPS (2023)
Tennison Liu, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar
Learning Representations without Compositional Assumptions. ICML (2023)
Alex J. Chan, Alihan Hüyük, Mihaela van der Schaar
Optimising Human-AI Collaboration by Learning Convincing Explanations. CoRR (2023)
Lasse Hansen, Nabeel Seedat, Mihaela van der Schaar, Andrija Petrovic
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark. CoRR (2023)
Aleksa Bisercic, Mladen Nikolic, Mihaela van der Schaar, Boris Delibasic, Pietro Liò, Andrija Petrovic
Interpretable Medical Diagnostics with Structured Data Extraction by Large Language Models. CoRR (2023)
Yuchao Qin, Mihaela van der Schaar, Changhee Lee
T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression. CoRR (2023)
Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data. NeurIPS (2023)
Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse, Dries Testelmans, Mihaela van der Schaar, Maarten De Vos
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging. CoRR (2023)
Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
Inverse Decision Modeling: Learning Interpretable Representations of Behavior. CoRR (2023)
Tennison Liu, Zhaozhi Qian, Jeroen Berrevoets, Mihaela van der Schaar
GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure. ICLR (2023)
Samuel Holt, Max Ruiz Luyten, Mihaela van der Schaar
L2MAC: Large Language Model Automatic Computer for Unbounded Code Generation. CoRR (2023)
Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
TRIAGE: Characterizing and auditing training data for improved regression. NeurIPS (2023)
Alicia Curth, Alan Jeffares, Mihaela van der Schaar
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning. CoRR (2023)
Alicia Curth, Mihaela van der Schaar
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data. AISTATS (2023)
Ioana Bica, Daniel Jarrett, Mihaela van der Schaar
Invariant Causal Imitation Learning for Generalizable Policies. CoRR (2023)
Alicia Curth, Mihaela van der Schaar
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation. ICML (2023)
Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar
Neural Laplace Control for Continuous-time Delayed Systems. CoRR (2023)
Fergus Imrie, Robert Davis, Mihaela van der Schaar
Multiple stakeholders drive diverse interpretability requirements for machine learning in healthcare. Nat. Mac. Intell. 5 (8) (2023)
Alicia Curth, Alan Jeffares, Mihaela van der Schaar
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning. NeurIPS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar
Joint Training of Deep Ensembles Fails Due to Learner Collusion. NeurIPS (2023)
Alicia Curth, Mihaela van der Schaar
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data. CoRR (2023)
Hao Sun, Alihan Hüyük, Mihaela van der Schaar
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL. CoRR (2023)
Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data. CoRR (2023)
Max Zhu, Katarzyna Kobalczyk, Andrija Petrovic, Mladen Nikolic, Mihaela van der Schaar, Boris Delibasic, Petro Liò
Tabular Few-Shot Generalization Across Heterogeneous Feature Spaces. CoRR (2023)
Fergus Imrie, Paulius Rauba, Mihaela van der Schaar
Redefining Digital Health Interfaces with Large Language Models. CoRR (2023)
Mahed Abroshan, Oscar Giles, Sam F. Greenbury, Jack Roberts, Mihaela van der Schaar, Jannetta S. Steyn, Alan Wilson, May Yong
Learning machines for health and beyond. CoRR (2023)
Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Liè, Mihaela van der Schaar
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. AISTATS (2023)
Toon Vanderschueren, Alicia Curth, Wouter Verbeke, Mihaela van der Schaar
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time. ICML (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization. ICLR (2023)
Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization. NeurIPS (2023)
Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
Time-series Generation by Contrastive Imitation. CoRR (2023)
Yuchao Qin, Mihaela van der Schaar, Changhee Lee
Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure. NeurIPS (2023)
Boris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar
Membership Inference Attacks against Synthetic Data through Overfitting Detection. CoRR (2023)
Trent Kyono, Ioana Bica, Zhaozhi Qian, Mihaela van der Schaar
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge. ACM Trans. Comput. Heal. 4 (2) (2023)
Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
Clairvoyance: A Pipeline Toolkit for Medical Time Series. CoRR (2023)
Alicia Curth, Alihan Hüyük, Mihaela van der Schaar
Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions. ICML (2023)
Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar
Deep Generative Symbolic Regression. ICLR (2023)
Yangming Li, Zhaozhi Qian, Mihaela van der Schaar
Do Diffusion Models Suffer Error Propagation? Theoretical Analysis and Consistency Regularization. CoRR (2023)
Boris van Breugel, Mihaela van der Schaar
Beyond Privacy: Navigating the Opportunities and Challenges of Synthetic Data. CoRR (2023)
Alicia Curth, Mihaela van der Schaar
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation. CoRR (2023)
Boris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar
Membership Inference Attacks against Synthetic Data through Overfitting Detection. AISTATS (2023)
Jonathan Crabbé, Mihaela van der Schaar
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance. NeurIPS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar
Joint Training of Deep Ensembles Fails Due to Learner Collusion. CoRR (2023)
Zhaozhi Qian, Robert Davis, Mihaela van der Schaar
Synthcity: a benchmark framework for diverse use cases of tabular synthetic data. NeurIPS (2023)
Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar
Neural Laplace Control for Continuous-time Delayed Systems. AISTATS (2023)
Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar
When to Make and Break Commitments? ICLR (2023)
Jeroen Berrevoets, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Differentiable and Transportable Structure Learning. ICML (2023)
Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Liò, Mihaela van der Schaar
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. CoRR (2023)
Boris van Breugel, Zhaozhi Qian, Mihaela van der Schaar
Synthetic data, real errors: how (not) to publish and use synthetic data. CoRR (2023)
Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
Online Decision Mediation. CoRR (2023)
Toon Vanderschueren, Alicia Curth, Wouter Verbeke, Mihaela van der Schaar
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time. CoRR (2023)
Evgeny S. Saveliev, Mihaela van der Schaar
TemporAI: Facilitating Machine Learning Innovation in Time Domain Tasks for Medicine. CoRR (2023)
Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar
Improving Adaptive Conformal Prediction Using Self-Supervised Learning. CoRR (2023)
Jeroen Berrevoets, Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar
Causal Deep Learning. CoRR (2023)
Hao Sun, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples. CoRR (2023)
Boris van Breugel, Zhaozhi Qian, Mihaela van der Schaar
Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data. ICML (2023)
Samuel Holt, Alihan Hüyük, Mihaela van der Schaar
Active Observing in Continuous-time Control. NeurIPS (2023)
Tennison Liu, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar
Learning Representations without Compositional Assumptions. CoRR (2023)
Yuchao Qin, Mihaela van der Schaar, Changhee Lee
T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression. AISTATS (2023)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mihaela van der Schaar