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Improving Event Time Prediction by Learning to Partition the Event Time Space
Recently developed survival analysis methods improve upon existing approaches by predicting the probability of event occurrence in each of a number pre-specified (discrete) time intervals.
Transfer Learning with Uncertainty Quantification: Random Effect Calibration of Source to Target (RECaST)
Most existing transfer learning approaches are based on fine-tuning pre-trained neural network models, and fail to provide crucial uncertainty quantification.
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