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Differentiable multi-target causal bayesian experimental design
We introduce a gradient-based approach for the problem of Bayesian optimal experimental
design to learn causal models in a batch setting—a critical component for causal discovery …
design to learn causal models in a batch setting—a critical component for causal discovery …
Differentiable multi-target causal bayesian experimental design
We introduce a gradient-based approach for the problem of Bayesian optimal experimental
design to learn causal models in a batch setting--a critical component for causal discovery …
design to learn causal models in a batch setting--a critical component for causal discovery …
Efficient Experimentation for Estimation of Continuous and Discrete Conditional Treatment Effects
Accurately estimating personalized treatment effects often demands substantial data,
incurring high costs across diverse applications such as personalized advertisement …
incurring high costs across diverse applications such as personalized advertisement …