LCD n-manifolds are linked to branched n-manifolds.
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We study the performance of Local Causal Discovery (LCD), a simple and efficient constraint-based method for causal discovery, in predicting causal effects in large-scale gene expression data. We construct practical estimators specific to the high-dimensional regime. Inspired by the ICP algorithm, we use an optional pr…
We address the problem of finding a minimal separator in an Andersson-Madigan-Perlman chain graph (AMP CG), namely, finding a set Z of nodes that separates a given nonadjacent pair of nodes such that no proper subset of Z separates that pair. We analyze several versions of this problem and offer polynomial-time algorit…
Causal effect estimation from observational data is an important and much studied research topic. The instrumental variable (IV) and local causal discovery (LCD) patterns are canonical examples of settings where a closed-form expression exists for the causal effect of one variable on another, given the presence of a th…
The paper investigates learning conditional distributions on multi-dimensional spaces using clustering and neural networks.
New method maps global value chains at product level from trade data.
The generalized Cartan-Hadamard conjecture says that if is a domain with fixed volume in a complete, simply connected Riemannian -manifold with sectional curvature , then the boundary of has the least possible boundary volume when is a round -ball with constant curvature . The c…