Mihaela van der Schaar

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 460

Top Venues

Publications

Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar
Adaptive Experiment Design with Synthetic Controls. CoRR (2024)
Jonathan Crabbé, Nicolas Huynh, Jan Stanczuk, Mihaela van der Schaar
Time Series Diffusion in the Frequency Domain. 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)
Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar
Large Language Models to Enhance Bayesian Optimization. CoRR (2024)
Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar
Deep Generative Symbolic Regression. CoRR (2024)
Thomas Pouplin, Hao Sun, Samuel Holt, Mihaela van der Schaar
Retrieval-Augmented Thought Process as Sequential Decision Making. CoRR (2024)
Alex J. Chan, Hao Sun, Samuel Holt, Mihaela van der Schaar
Dense Reward for Free in Reinforcement Learning from Human Feedback. CoRR (2024)
Yangming Li, Max Ruiz Luyten, Mihaela van der Schaar
Risk-Sensitive Diffusion: Learning the Underlying Distribution from Noisy Samples. 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)
Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz
Machine Learning with Requirements: a Manifesto. CoRR (2023)
Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar
To Impute or not to Impute? Missing Data in Treatment Effect Estimation. AISTATS (2023)
Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
TRIAGE: Characterizing and auditing training data for improved regression. CoRR (2023)
Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar
Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning. CoRR (2023)
Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR (2023)
Lasse Hansen, Nabeel Seedat, Mihaela van der Schaar, Andrija Petrovic
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark. NeurIPS (2023)
Nabeel Seedat, Nicolas Huynh, Boris van Breugel, Mihaela van der Schaar
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in ultra low-data regimes. CoRR (2023)
Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar
D-CIPHER: Discovery of Closed-form Partial Differential Equations. NeurIPS (2023)
Jonathan Crabbé, Mihaela van der Schaar
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance. CoRR (2023)
Hao Sun, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples. NeurIPS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization. CoRR (2023)
Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar
Improving Adaptive Conformal Prediction Using Self-Supervised Learning. AISTATS (2023)
Mahed Abroshan, Kai Hou Yip, Cem Tekin, Mihaela van der Schaar
Conservative Policy Construction Using Variational Autoencoders for Logged Data With Missing Values. IEEE Trans. Neural Networks Learn. Syst. 34 (9) (2023)
Tim Schubert, Richard W. Peck, Alexander Gimson, Camelia Davtyan, Mihaela van der Schaar
A Foundational Framework and Methodology for Personalized Early and Timely Diagnosis. CoRR (2023)
Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar
A Neural Framework for Generalized Causal Sensitivity Analysis. CoRR (2023)
Hao Sun, Alex J. Chan, Nabeel Seedat, Alihan Hüyük, Mihaela van der Schaar
When is Off-Policy Evaluation Useful? A Data-Centric Perspective. CoRR (2023)
Zhaozhi Qian, Bogdan-Constantin Cebere, Mihaela van der Schaar
Synthcity: facilitating innovative use cases of synthetic data in different data modalities. CoRR (2023)
Onur Atan, Saeed Ghoorchian, Setareh Maghsudi, Mihaela van der Schaar
Data-Driven Online Recommender Systems With Costly Information Acquisition. IEEE Trans. Serv. Comput. 16 (1) (2023)
Yangming Li, Boris van Breugel, Mihaela van der Schaar
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models. CoRR (2023)
Alihan Hüyük, William R. Zame, Mihaela van der Schaar
Inferring Lexicographically-Ordered Rewards from Preferences. CoRR (2022)
Fergus Imrie, Alexander Norcliffe, Pietro Lió, Mihaela van der Schaar
Composite Feature Selection Using Deep Ensembles. NeurIPS (2022)
Jeroen Berrevoets, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Differentiable and Transportable Structure Learning. CoRR (2022)
Zhaozhi Qian, Krzysztof Kacprzyk, Mihaela van der Schaar
D-CODE: Discovering Closed-form ODEs from Observed Trajectories. ICLR (2022)
Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
Online Decision Mediation. NeurIPS (2022)
Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar
Neural Laplace: Learning diverse classes of differential equations in the Laplace domain. ICML (2022)
Alex J. Chan, Mihaela van der Schaar
Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning. CoRR (2022)
Alizée Pace, Alex Chan, Mihaela van der Schaar
POETREE: Interpretable Policy Learning with Adaptive Decision Trees. ICLR (2022)
Daniel Jarrett, Bogdan Cebere, Tennison Liu, Alicia Curth, Mihaela van der Schaar
HyperImpute: Generalized Iterative Imputation with Automatic Model Selection. CoRR (2022)
Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar
D-CIPHER: Discovery of Closed-form PDEs. CoRR (2022)
Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. NeurIPS (2022)
Changhee Lee, Fergus Imrie, Mihaela van der Schaar
Self-Supervision Enhanced Feature Selection with Correlated Gates. ICLR (2022)
Ioana Bica, Mihaela van der Schaar
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation. NeurIPS (2022)
Cong Shen, Zhaozhi Qian, Alihan Hüyük, Mihaela van der Schaar
MARS: Assisting Human with Information Processing Tasks Using Machine Learning. ACM Trans. Comput. Heal. 3 (2) (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mihaela van der Schaar