ADHAM combines additive per-covariate hazard functions with latent subgroup mixtures, and a post-training refinement merges similar subgroups without retraining.
Can we gain more from orthogonality regularizations in training deep networks? Advances in Neural Information Processing Systems, 31, 2018
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ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression
ADHAM combines additive per-covariate hazard functions with latent subgroup mixtures, and a post-training refinement merges similar subgroups without retraining.