Conditional Tensor Diffusion: Distributional Counterfactual Learning and Inference
Counterfactual Tucker Diffusion (CFTDiff), which integrates the treatment mask and latent Tucker structure into conditional diffusion to recover this distribution given observed control outcomes through efficient nonlinear score learning in a low-dimensional core, and establishes high-probability error bounds.