User profiles for Mihaela van der Schaar
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing Institute Verified email at ee.ucla.edu Cited by 31192 |
Time-series generative adversarial networks
…, D Jarrett, M Van der Schaar - Advances in neural …, 2019 - proceedings.neurips.cc
A good generative model for time-series data should preserve temporal dynamics, in the
sense that new sequences respect the original relationships between variables across time. …
sense that new sequences respect the original relationships between variables across time. …
From real‐world patient data to individualized treatment effects using machine learning: current and future methods to address underlying challenges
…, C Lambert, M Van Der Schaar - Clinical Pharmacology …, 2021 - Wiley Online Library
… Alaa and van der Schaar 22, 60 developed a unifying theory highlighting the fundamental
… Alaa and van der Schaar 21 evaluate the CMGP model on estimating the survival benefits of …
… Alaa and van der Schaar 21 evaluate the CMGP model on estimating the survival benefits of …
[HTML][HTML] Ethnic and regional variations in hospital mortality from COVID-19 in Brazil: a cross-sectional observational study
Background Brazil ranks second worldwide in total number of COVID-19 cases and deaths.
Understanding the possible socioeconomic and ethnic health inequities is particularly …
Understanding the possible socioeconomic and ethnic health inequities is particularly …
PATE-GAN: Generating synthetic data with differential privacy guarantees
Machine learning has the potential to assist many communities in using the large datasets
that are becoming more and more available. Unfortunately, much of that potential is not being …
that are becoming more and more available. Unfortunately, much of that potential is not being …
Deephit: A deep learning approach to survival analysis with competing risks
Survival analysis (time-to-event analysis) is widely used in economics and finance,
engineering, medicine and many other areas. A fundamental problem is to understand the …
engineering, medicine and many other areas. A fundamental problem is to understand the …
A machine learning approach for tracking and predicting student performance in degree programs
…, KH Moon, M Van Der Schaar - IEEE Journal of Selected …, 2017 - ieeexplore.ieee.org
Accurately predicting students’ future performance based on their ongoing academic records
is crucial for effectively carrying out necessary pedagogical interventions to ensure students…
is crucial for effectively carrying out necessary pedagogical interventions to ensure students…
GANITE: Estimation of individualized treatment effects using generative adversarial nets
Estimating individualized treatment effects (ITE) is a challenging task due to the need for an
individual's potential outcomes to be learned from biased data and without having access to …
individual's potential outcomes to be learned from biased data and without having access to …
[HTML][HTML] Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants
Background Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of
preventative cardiology. Risk prediction models currently recommended by clinical …
preventative cardiology. Risk prediction models currently recommended by clinical …
Deep generative models for 3D linker design
Rational compound design remains a challenging problem for both computational methods
and medicinal chemists. Computational generative methods have begun to show promising …
and medicinal chemists. Computational generative methods have begun to show promising …
Machine learning in the air
…, CR Murthy, M van der Schaar - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Thanks to the recent advances in processing speed, data acquisition and storage, machine
learning (ML) is penetrating every facet of our lives, and transforming research in many …
learning (ML) is penetrating every facet of our lives, and transforming research in many …