ProjectCausal / discoveryNeurIPS 2025★ Featured
CausalPFN
Pretrained causal-effect PFN · test it on your data
Balazadeh, Kamkari, Thomas et al. 2025 · CausalPFNApache-2.0
Use this to test causal-effect estimation on your own observational data: covariates, a treatment / decision column, and an outcome. It returns a per-unit effect (CATE) and an average effect (ATE) in-context. Inference-only — for a trainable causal base model, pick Do-PFN or TCPFN.