Raphael Rehms

Clinical histories are fundamentally irregular and multimodal, yet foundation models have treated them as static or uniformly discrete—until a generative variational transformer trained on 559 million events unified continuous-time forecasting, multi-modal health records, and counterfactual intervention simulation.

Jointly modeling aleatoric and epistemic uncertainties can dramatically enhance prediction reliability in high-dimensional outputs, outperforming traditional methods.