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Showing 1 to 7 of 7 for “"Gibbs distribution"”.

  1. DEUM: a framework for an estimation of distribution algorithm based on Markov random fields.

    Estimation of Distribution Algorithms (EDAs) belong to the class of population based optimisation algorithms. They are motivated by the idea of discovering and exploiting the interaction between variables in the solution. They estimate a probability distribution from population of solutions, and …

    rgu Repository record for DEUM: a framework for an estimation of distribution algorithm based on Markov random fields. (opens in a new tab)

  2. Introduction to the Glauber dynamics for the Curie-Weiss Potts model

    … of simulating configurations according to the Gibbs distribution of the Curie-Weiss Potts model. Therefore, essential aspects of discrete-time Markov chains on a finite state space are examined, especially their convergence behavior and related mixing times. Furthermore, special emphasis is …

    potsdam-thes Repository record for Introduction to the Glauber dynamics for the Curie-Weiss Potts model (opens in a new tab)

  3. Greedy Inference Algorithms for Structured and Neural Models

    … deterministic samples that are representative of Gibbs distribution via a greedy strategy. 2) Searching for a set of diverse and high-quality bounding boxes. We formulate this problem as the constrained maximization of a monotonic sub-modular function such that there exists a greedy algorithm …

    vt Repository record for Greedy Inference Algorithms for Structured and Neural Models (opens in a new tab)

  4. Homogenization of Random Media: Random Walks, Diffusions and Stochastic Interface Models

    … model. We also show that the associated Gibbs distribution scales to a Gaussian free field. In the final chapter, we study a symmetric diffusion process in divergence form in a stationary and ergodic random environment. This is a continuum analogue of the random conductance model and …

    cambridge Repository record for Homogenization of Random Media: Random Walks, Diffusions and Stochastic Interface Models (opens in a new tab)

  5. Designing Provably Convergent Algorithms from the Geometry of Data

    … consider sampling, as sampling from a Gibbs distribution, and as a universal data preprocessing method for machine learning. (iv) We derive a principled score approximator using Wasserstein proximals of distributions, bypassing the requirement of choosing an appropriate kernel or learn …

    cambridge Repository record for Designing Provably Convergent Algorithms from the Geometry of Data (opens in a new tab)

  6. Novel Monte Carlo Approaches to Identify Aberrant Pathways in Cancer

    … pathways. We propose a robust method, called GibbsOS, to identify condition specific gene regulatory patterns between transcription factors and their target genes. A Gibbs sampler is employed to sample target genes from the marginal function of outlier sum of regression t statistic. Numerical …

    vt Repository record for Novel Monte Carlo Approaches to Identify Aberrant Pathways in Cancer (opens in a new tab)

  7. Tools and Techniques for Evaluating Reliability Trade-offs for Nano-Architectures

    It is expected that nano-scale devices and interconnections will introduce unprecedented level of defects in the substrates, and architectural designs need to accommodate the uncertainty inherent at such scales. This consideration motivates the search for new architectural paradigms based on …

    vt Repository record for Tools and Techniques for Evaluating Reliability Trade-offs for Nano-Architectures (opens in a new tab)