Abstract: In this letter, we present an approach for learning a neural implicit signed distance function expressed in joint space coordinates, that efficiently computes distance-to-collisions for ...

Abstract: Recently, the single image super-resolution based on implicit image function is a hot topic, which learns a universal model for arbitrary upsampling scales. By contrast, color-guided depth ...

Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States ...

Integrating human values after model training using Learning-based algorithms requires fine-tuning LLMs, which requires more computational power and is time-consuming. Additionally, it generates ...

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ABSTRACT: Considered under their standard form, the fifth-order KdV equations are a sort of reading table on which new prototypes of higher order solitary waves residing there, have been uncovered and ...

We introduce two new language features, called implicit functions and implicit control. Both generalize implicit values (or parameters) which are a typed implementation of dynamic binding. Implicit ...

"By treating the solution $\\phi^{\\star}$ as an implicit function of $\\theta$, the idea of implicit differentiation is to directly get analytical best-response derivatives $\\partial \\phi^{\\star}( ...