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06/10/2023
Functional Causal Bayesian Optimization
We propose functional causal Bayesian optimization (fCBO), a method for ...
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06/16/2022
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations
Estimating counterfactual outcomes over time has the potential to unlock...
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05/29/2022
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage
We investigate the task of estimating the conditional average causal eff...
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11/04/2021
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms
Missing data is an important problem in machine learning practice. Start...
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05/06/2021
Consistency of mechanistic causal discovery in continuous-time using Neural ODEs
The discovery of causal mechanisms from time series data is a key proble...
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03/28/2021
Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding
Unobserved confounding is one of the greatest challenges for causal disc...
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02/02/2021
Policy Analysis using Synthetic Controls in Continuous-Time
Counterfactual estimation using synthetic controls is one of the most su...
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07/21/2020
Generalization and Invariances in the Presence of Unobserved Confounding
The ability to extrapolate, or generalize, from observed to new related ...
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01/14/2020
Learning Overlapping Representations for the Estimation of Individualized Treatment Effects
The choice of making an intervention depends on its potential benefit or...
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01/08/2020
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes
Comorbid diseases co-occur and progress via complex temporal patterns th...
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12/19/2019
A Bayesian Approach to Modelling Longitudinal Data in Electronic Health Records
Analyzing electronic health records (EHR) poses significant challenges b...
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07/09/2019
A Robust Two-Sample Test for Time Series data
We develop a general framework for hypothesis testing with time series d...
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07/09/2019