90 citations · 253 across the 12 of their papers we have counts for
18 papers
Learning Matching Representations for Individualized Organ Transplantation Allocation
Can Xu, Ahmed M. Alaa, Ioana Bica +3
Organ transplantation is often the last resort for treating end-stage illness, but the probability of a successful transplantation depends greatly on compatibility between donors a…
Estimating Structural Target Functions using Machine Learning and Influence Functions
Alicia Curth, Ahmed M. Alaa, Mihaela van der Schaar
We aim to construct a class of learning algorithms that are of practical value to applied researchers in fields such as biostatistics, epidemiology and econometrics, where the need…
CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19
Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar
The coronavirus disease 2019 (COVID-19) global pandemic poses the threat of overwhelming healthcare systems with unprecedented demands for intensive care resources. Managing these…
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions
Ahmed M. Alaa, Mihaela van der Schaar
Deep learning models achieve high predictive accuracy across a broad spectrum of tasks, but rigorously quantifying their predictive uncertainty remains challenging. Usable estimate…
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions
Ahmed M. Alaa, Mihaela van der Schaar
Recurrent neural networks (RNNs) are instrumental in modelling sequential and time-series data. Yet, when using RNNs to inform decision-making, predictions by themselves are not su…
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift
Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian +1
Modern neural networks have proven to be powerful function approximators, providing state-of-the-art performance in a multitude of applications. They however fall short in their ab…