TNPA uses tensor-network contractions only in a reliable temperature window to seed population annealing, with an effective-sample-size diagnostic to pick the switch-over temperature.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Active Model B+ exhibits mean-field critical scaling identical to AMB and supercritical coarsening with logarithmic corrections to t^{1/3} growth that are suppressed by active currents, leading to arrested microphase separation.
Tempered posteriors combined with Wang-Landau sampling identify transition temperatures that optimize predictive performance in Bayesian inference for real-world problems.
citing papers explorer
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Tensor-Network Population Annealing
TNPA uses tensor-network contractions only in a reliable temperature window to seed population annealing, with an effective-sample-size diagnostic to pick the switch-over temperature.
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Critical scaling and supercritical coarsening in Active Model B+
Active Model B+ exhibits mean-field critical scaling identical to AMB and supercritical coarsening with logarithmic corrections to t^{1/3} growth that are suppressed by active currents, leading to arrested microphase separation.
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Using Statistical Mechanics to Improve Real-World Bayesian Inference: A New Method Combining Tempered Posteriors and Wang-Landau Sampling
Tempered posteriors combined with Wang-Landau sampling identify transition temperatures that optimize predictive performance in Bayesian inference for real-world problems.