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Showing 1 to 5 of 5 for “"guided sampling"”.

  1. New algorithmic developments in maximum consensus robust fitting

    … estimates. To improve the randomize algorithms, guided sampling approaches have been developed. These methods take advantage of additional domain information, such as descriptor matching scores, to guide the sampling process. Subsets of the data that are more likely to result in good estimates …

    adelaide Repository record for New algorithmic developments in maximum consensus robust fitting (opens in a new tab)

  2. Sampling and Searching Methods for Practical Motion Planning Algorithms

    … part due to the development of highly successful sampling and searching techniques. Recent advances have influenced sampling-based motion planning algorithms to be used in disparate areas such as humanoid robotics, automotive manufacturing, spacecraft navigation, architecture, computational …

    uiuc Repository record for Sampling and Searching Methods for Practical Motion Planning Algorithms (opens in a new tab)

  3. Guiding diffusion generative models with applications to inverse problems

    Conditional sampling via denoising diffusion models (DDMs) has received significant interest in generative modelling for their scalability, improved sample quality, and versatile application. These models are widely used in scientific and industrial settings, where they leverage latent …

    cambridge Repository record for Guiding diffusion generative models with applications to inverse problems (opens in a new tab)

  4. Improving the consistency of nonlinear estimators: analysis, algorithms, and applications

    … filters (PFs) and develop an Analytically-Guided-Sampling (AGS)-PF. Specifically, the AGS-PF employs an analytically-determined Gaussian mixture as proposal distribution which not only takes into account the most recent measurement but also matches all the modes of the posterior (optimal …

    umn Repository record for Improving the consistency of nonlinear estimators: analysis, algorithms, and applications (opens in a new tab)

  5. Validated global multiobjective optimization of trajectories in nonlinear dynamical systems

    … programming), combined with stochastic or expert-guided sampling to seek global optimality. This approach substantially relies on pre-existing intuition about the character of optimal solutions, and provides no guarantees on the global optimality of solutions obtained. The requirements for expert …

    mit Repository record for Validated global multiobjective optimization of trajectories in nonlinear dynamical systems (opens in a new tab)