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Mihaela van der Schaar - Causal Deep Learning
Mihaela van der Schaar
Sat Jul 29 12:10 PM -- 12:30 PM (PDT) @
Author Information
Mihaela van der Schaar (University of Cambridge and UCLA)
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2021 : Doing Great at Estimating CATE? On the Neglected Assumptions in Benchmark Comparisons of Treatment Effect Estimators »
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2023 : Keynote 2: Mihaela van der Schaar (University of Cambridge) - Reality-Centric AI »
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2023 Poster: Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data »
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2023 Poster: Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions »
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2023 Poster: In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation »
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2023 Poster: Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time »
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2023 Poster: Learning Representations without Compositional Assumptions »
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2023 Poster: Differentiable and Transportable Structure Learning »
Jeroen Berrevoets · Nabeel Seedat · Fergus Imrie · Mihaela van der Schaar -
2022 Poster: Inverse Contextual Bandits: Learning How Behavior Evolves over Time »
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2022 Poster: Data-SUITE: Data-centric identification of in-distribution incongruous examples »
Nabeel Seedat · Jonathan Crabbé · Mihaela van der Schaar -
2022 Poster: Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations »
Nabeel Seedat · Fergus Imrie · Alexis Bellot · Zhaozhi Qian · Mihaela van der Schaar -
2022 Spotlight: Data-SUITE: Data-centric identification of in-distribution incongruous examples »
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2022 Spotlight: Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations »
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2022 Spotlight: Inverse Contextual Bandits: Learning How Behavior Evolves over Time »
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2022 Poster: Label-Free Explainability for Unsupervised Models »
Jonathan Crabbé · Mihaela van der Schaar -
2022 Poster: HyperImpute: Generalized Iterative Imputation with Automatic Model Selection »
Daniel Jarrett · Bogdan Cebere · Tennison Liu · Alicia Curth · Mihaela van der Schaar -
2022 Spotlight: HyperImpute: Generalized Iterative Imputation with Automatic Model Selection »
Daniel Jarrett · Bogdan Cebere · Tennison Liu · Alicia Curth · Mihaela van der Schaar -
2022 Spotlight: Label-Free Explainability for Unsupervised Models »
Jonathan Crabbé · Mihaela van der Schaar -
2022 Poster: How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models »
Ahmed Alaa · Boris van Breugel · Evgeny S. Saveliev · Mihaela van der Schaar -
2022 Poster: Neural Laplace: Learning diverse classes of differential equations in the Laplace domain »
Samuel Holt · Zhaozhi Qian · Mihaela van der Schaar -
2022 Oral: Neural Laplace: Learning diverse classes of differential equations in the Laplace domain »
Samuel Holt · Zhaozhi Qian · Mihaela van der Schaar -
2022 Spotlight: How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models »
Ahmed Alaa · Boris van Breugel · Evgeny S. Saveliev · Mihaela van der Schaar -
2022 Expo Talk Panel: Machine learning for drug discovery: Challenges and opportunities »
Mihaela van der Schaar · Jian Tang · A Martin Jones · Sébastien Lemieux · Thomas Watson -
2021 : Mihaela Van der Schaar: Time-series in healthcare: challenges and solutions »
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2021 Workshop: Self-Supervised Learning for Reasoning and Perception »
Pengtao Xie · Shanghang Zhang · Ishan Misra · Pulkit Agrawal · Katerina Fragkiadaki · Ruisi Zhang · Tassilo Klein · Asli Celikyilmaz · Mihaela van der Schaar · Eric Xing -
2021 : Quantitative epistemology: conceiving a new human-machine partnership »
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2021 Poster: Explaining Time Series Predictions with Dynamic Masks »
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2021 Spotlight: Explaining Time Series Predictions with Dynamic Masks »
Jonathan Crabbé · Mihaela van der Schaar -
2021 Poster: Policy Analysis using Synthetic Controls in Continuous-Time »
Alexis Bellot · Mihaela van der Schaar -
2021 Spotlight: Policy Analysis using Synthetic Controls in Continuous-Time »
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2021 Poster: Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis »
Jeroen Berrevoets · Ahmed Alaa · Zhaozhi Qian · James Jordon · alexander gimson · Mihaela van der Schaar -
2021 Spotlight: Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis »
Jeroen Berrevoets · Ahmed Alaa · Zhaozhi Qian · James Jordon · alexander gimson · Mihaela van der Schaar -
2021 Poster: Inverse Decision Modeling: Learning Interpretable Representations of Behavior »
Daniel Jarrett · Alihan Hüyük · Mihaela van der Schaar -
2021 Oral: Inverse Decision Modeling: Learning Interpretable Representations of Behavior »
Daniel Jarrett · Alihan Hüyük · Mihaela van der Schaar -
2021 Tutorial: Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning »
Ahmed M. Alaa · Mihaela van der Schaar -
2021 : Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning »
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2020 : Panel Discussion »
Neil Lawrence · Mihaela van der Schaar · Alex Smola · Valerio Perrone · Jack Parker-Holder · Zhengying Liu -
2020 : "Automated ML and its transformative impact on medicine and healthcare" by Mihaela van der Schaar »
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2020 : Invited Talk: Learning despite the unknown - missing data imputation in healthcare »
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2020 Poster: Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift »
Alexander Chan · Ahmed Alaa · Zhaozhi Qian · Mihaela van der Schaar -
2020 Poster: Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions »
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2020 Poster: Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders »
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2020 Poster: Temporal Phenotyping using Deep Predictive Clustering of Disease Progression »
Changhee Lee · Mihaela van der Schaar -
2020 Poster: Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints »
Cong Shen · Zhiyang Wang · Sofia Villar · Mihaela van der Schaar -
2020 Poster: Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions »
Ahmed Alaa · Mihaela van der Schaar -
2020 Poster: Inverse Active Sensing: Modeling and Understanding Timely Decision-Making »
Daniel Jarrett · Mihaela van der Schaar -
2020 Tutorial: Machine Learning for Healthcare: Challenges, Methods, Frontiers »
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2019 Poster: Validating Causal Inference Models via Influence Functions »
Ahmed Alaa · Mihaela van der Schaar -
2019 Oral: Validating Causal Inference Models via Influence Functions »
Ahmed Alaa · Mihaela van der Schaar -
2018 Poster: AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning »
Ahmed M. Alaa · Mihaela van der Schaar -
2018 Oral: AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning »
Ahmed M. Alaa · Mihaela van der Schaar -
2018 Poster: Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design »
Ahmed M. Alaa · Mihaela van der Schaar -
2018 Oral: Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design »
Ahmed M. Alaa · Mihaela van der Schaar -
2017 Poster: Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis »
Ahmed M. Alaa · Scott B Hu · Mihaela van der Schaar -
2017 Talk: Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis »
Ahmed M. Alaa · Scott B Hu · Mihaela van der Schaar