Results 31 to 40 of about 13,863,270 (332)
Continuous Regular Functions [PDF]
Following Chaudhuri, Sankaranarayanan, and Vardi, we say that a function $f:[0,1] \to [0,1]$ is $r$-regular if there is a B\"{u}chi automaton that accepts precisely the set of base $r \in \mathbb{N}$ representations of elements of the graph of $f$.
Alexi Block Gorman +7 more
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We present a method based on combining a smooth generalized pinball support vector machine (SVM) and variational autoencoders (VAEs) in chest X-ray (CXR) images.
Wachiraphong Ratiphaphongthon +2 more
doaj +1 more source
A Language for Differentiable Functions [PDF]
We introduce a typed lambda calculus in which real numbers, real functions, and in particular continuously differentiable and more generally Lipschitz functions can be defined. Given an expression representing a real-valued function of a real variable in this calculus, we are able to evaluate the expression on an argument but also evaluate the L ...
DI GIANANTONIO, Pietro, Abbas Edalat
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A Note on Differentiable Functions [PDF]
This paper provides a proof that the class of those real functions f for which there exists a change of variable g so that f
Fleissner, Richard J., Foran, James
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Chaotic intermittency with non-differentiable M(x) function
One-dimensional maps showing chaotic intermittency with discontinuous reinjection probability density functions are studied. For these maps, the reinjection mechanism possesses two different processes.
Sergio Elaskar +2 more
doaj +1 more source
The differentiation of a function of a function [PDF]
If z is a function of y having a differential coefficient at a certain point, and y is a function of x having a differential coefficient at the corresponding point, then z is a function of x having a differential coefficient at that point, and this differential coefficient is given by the formula
openaire +3 more sources
Soft Rasterizer: A Differentiable Renderer for Image-Based 3D Reasoning [PDF]
Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical process of image formation. By inverting such renderer, one can think of a learning approach to infer 3D information from 2D images. However, standard graphics renderers
Shichen Liu +3 more
semanticscholar +1 more source
Riemann's non-differentiable function is intermittent [PDF]
Riemann's non-differentiable function, introduced in the middle of the 19th century as a purely mathematical pathological object, is relevant in the study of the binormal flow, as shown recently by De La Hoz and Vega.
Eceizabarrena, Daniel +2 more
core +2 more sources
Implications of Non-Differentiable Entropy on a Space-Time Manifold
Assuming that the motions of a complex system structural units take place on continuous, but non-differentiable curves of a space-time manifold, the scale relativity model with arbitrary constant fractal dimension (the hydrodynamic and wave function ...
Maricel Agop +3 more
doaj +1 more source
Differentiable surface splatting for point-based geometry processing [PDF]
We propose Differentiable Surface Splatting (DSS), a high-fidelity differentiable renderer for point clouds. Gradients for point locations and normals are carefully designed to handle discontinuities of the rendering function.
Yifan Wang +4 more
semanticscholar +1 more source

