EFE-based planning is formulated as variational free energy minimization with epistemic priors, decomposing into expected plan costs plus a complexity term.
Title resolution pending
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
verdicts
UNVERDICTED 5roles
method 1polarities
use method 1representative citing papers
BOO achieves exponentially decaying regret O(N^{-√N}) by combining Bayesian optimisation and partitioning-based optimistic optimisation for Matérn GP functions with ν > 4 + D/2.
A framework maps erosion distributions to Wasserstein space, uses basis expansion to create a multivariate random field, and applies local regression plus Kriging to predict distributions and their functionals at new locations, outperforming alternatives in simulations and applied to Shaanxi provinc
Two-dimensional filtering of spatially uncorrelated white noise generates red along-track spectra in SWOT observations, matching observed power-law behavior at small scales.
Neural feature maps create expressive kernels that enable fast, scalable, and consistent exact Gaussian process inference for regression and classification.
citing papers explorer
-
Expected Free Energy-based Planning as Variational Inference
EFE-based planning is formulated as variational free energy minimization with epistemic priors, decomposing into expected plan costs plus a complexity term.
-
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
BOO achieves exponentially decaying regret O(N^{-√N}) by combining Bayesian optimisation and partitioning-based optimistic optimisation for Matérn GP functions with ν > 4 + D/2.
-
Spatial Prediction of Local Soil Erosion Distribution in the Wasserstein Space
A framework maps erosion distributions to Wasserstein space, uses basis expansion to create a multivariate random field, and applies local regression plus Kriging to predict distributions and their functionals at new locations, outperforming alternatives in simulations and applied to Shaanxi provinc
-
The impact of two-dimensional filtering on white noise spectra in SWOT along-track observations
Two-dimensional filtering of spatially uncorrelated white noise generates red along-track spectra in SWOT observations, matching observed power-law behavior at small scales.
-
Scalable Gaussian process inference via neural feature maps
Neural feature maps create expressive kernels that enable fast, scalable, and consistent exact Gaussian process inference for regression and classification.