Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles

arXiv:2609.29974 · cs.LG · Submitted 2026-09-24 · Read on arXiv

cs.LG

Submitted: 2026-09-24

Updated: 2026-09-25

Code: https://github.com/WeijiaZhang24/TEDVAE

Terminology

• Benchmark — 63× in this paper · explained in 2 episodes
• Aggregation — 26× in this paper · explained in 1 episode
• Causal Inference — 7× in this paper · explained in 4 episodes
• Regularization — 7× in this paper · explained in 3 episodes
• Calibration — 6× in this paper · explained in 7 episodes
• Exchangeability — 5× in this paper · explained in 2 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Meta-learning — 3× in this paper · explained in 2 episodes
• Provenance — 3× in this paper · explained in 3 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Bayesian Inference — 2× in this paper · explained in 5 episodes
• Residualization — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generalization Bounds — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Mixture of Experts — 1× in this paper · explained in 2 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Regret — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017

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