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stat.ML2025
Intervening to Learn and Compose Causally Disentangled Representations
Alex Markham, Isaac Hirsch, Jeri A. Chang +2
In designing generative models, it is commonly believed that in order to learn useful latent structure, we face a fundamental tension between expressivity and structure. In this pa…
stat.ML2025
Addressing pitfalls in implicit unobserved confounding synthesis using explicit block hierarchical ancestral sampling
Xudong Sun, Alex Markham, Pratik Misra +1
Unbiased data synthesis is crucial for evaluating causal discovery algorithms in the presence of unobserved confounding, given the scarcity of real-world datasets. A common approac…