Fig. 1.

The BITES network architecture. BITES uses shared deeply connected layers for both treatment options, which are mapped on a latent representation $\Phi$. This is regularized by a Sinkhorn divergence to account for imbalances between treatment and control distributions. The factual and counterfactual proportional hazard rates are modeled by two different outcome heads (h₁ and h₀), respectively. These are used to predict the ITE together with the corresponding baseline hazard function. The latter is individually estimated for treatment and control patients