Tag: graphs
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Distributional Computational Graphs: Error Bounds
Distributional Computational Graphs: Error Bounds arXiv:2601.16250v1 Announce Type: new Abstract: We study a general framework of distributional computational graphs: computational graphs whose inputs are probability distributions rather than point values. We analyze the discretization error that arises when these graphs are evaluated using finite approximations of continuous probability distributions. Such an approximation might be the…
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A pseudo-inverse of a line graph
A pseudo-inverse of a line graph arXiv:2508.09412v1 Announce Type: new Abstract: Line graphs are an alternative representation of graphs where each vertex of the original (root) graph becomes an edge. However not all graphs have a corresponding root graph, hence the transformation from graphs to line graphs is not invertible. We investigate the case when…
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Characterization and Learning of Causal Graphs from Hard Interventions
Characterization and Learning of Causal Graphs from Hard Interventions arXiv:2505.01037v1 Announce Type: new Abstract: A fundamental challenge in the empirical sciences involves uncovering causal structure through observation and experimentation. Causal discovery entails linking the conditional independence (CI) invariances in observational data to their corresponding graphical constraints via d-separation. In this paper, we consider a general…