Glauber dynamics
PulseAugur coverage of Glauber dynamics — every cluster mentioning Glauber dynamics across labs, papers, and developer communities, ranked by signal.
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New algorithms offer signal-optimal learning for Gaussian graphical models
Researchers have developed two novel algorithms for learning Gaussian graphical models from data generated by a single trajectory of a dependent stochastic process, specifically random-scan Gaussian Glauber dynamics. Th…
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New algorithm learns constant-depth circuits under locally sampleable graphical models
Researchers have developed a new algorithm for learning constant-depth circuits under graphical models that can be locally sampled. This work extends previous findings by Chandrasekaran, Gaitonde, Moitra, and Vasilyan (…
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New algorithm learns Gaussian graphical models from single trajectory
Researchers have developed a new polynomial-time algorithm capable of recovering the conditional-independence graph of a Gaussian graphical model from a single trajectory of Glauber dynamics. This method does not requir…
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New algorithms tackle Gaussian graphical model selection from dependent data
Researchers have developed new algorithms for Gaussian graphical model selection when data comes from dependent dynamics, rather than independent samples. One approach uses a local edge-testing estimator that can be imp…