AINeutralarXiv – CS AI · 11h ago6/10
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ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
Researchers introduce ACTIVA, a transformer-based variational autoencoder designed to estimate causal interventional distributions from observational data without requiring intervention datasets. The model amortizes causal knowledge across tasks, enabling zero-shot inference and outperforming existing baselines on synthetic and biological datasets while reducing spurious correlations.