30 citations · 42 across the 4 of their papers we have counts for
4 papers
To Impute or not to Impute? Missing Data in Treatment Effect Estimation
Jeroen Berrevoets, Fergus Imrie, Trent Kyono +2
Missing data is a systemic problem in practical scenarios that causes noise and bias when estimating treatment effects. This makes treatment effect estimation from data with missin…
Improving Model Robustness Using Causal Knowledge
Trent Kyono, Mihaela van der Schaar
For decades, researchers in fields, such as the natural and social sciences, have been verifying causal relationships and investigating hypotheses that are now well-established or…
MAMMO: A Deep Learning Solution for Facilitating Radiologist-Machine Collaboration in Breast Cancer Diagnosis
Trent Kyono, Fiona J. Gilbert, Mihaela van der Schaar
With an aging and growing population, the number of women requiring either screening or symptomatic mammograms is increasing. To reduce the number of mammograms that need to be rea…
Siamese Survival Analysis with Competing Risks
Anton Nemchenko, Trent Kyono, Mihaela Van Der Schaar
Survival analysis in the presence of multiple possible adverse events, i.e., competing risks, is a pervasive problem in many industries (healthcare, finance, etc.). Since only one…