For Erdős-Rényi random graphs the d-dimensional realization count is infinity or 2^k with k polynomial-time computable; analogous result for generic PSD matrix completion.
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3 Pith papers cite this work. Polarity classification is still indexing.
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A two-level low-rank approximation enables scalable A-optimal sensor design for passive imaging without repeated PDE solves in the online phase.
Coverage tests for simulation-based inference of f_NL can pass while the posteriors are underconfident in the tails and sometimes yield weaker constraints than using power spectrum or bispectrum alone.
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The number of realisations of a random graph
For Erdős-Rényi random graphs the d-dimensional realization count is infinity or 2^k with k polynomial-time computable; analogous result for generic PSD matrix completion.
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Optimal experimental design for passive imaging source problems
A two-level low-rank approximation enables scalable A-optimal sensor design for passive imaging without repeated PDE solves in the online phase.
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Coverage is not enough: Frequentist tests of simulation-based inference for primordial non-Gaussianity
Coverage tests for simulation-based inference of f_NL can pass while the posteriors are underconfident in the tails and sometimes yield weaker constraints than using power spectrum or bispectrum alone.