Results 311 to 320 of about 12,319,152 (351)

SoftAlign: End-to-end protein structures alignment

Trinquier J, Petti S, Park S, Herath K, van Kempen M, Feng S, Söding J, Steinegger M, Ovchinnikov S.   +8 more
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Differentiable signed distance function rendering

ACM Transactions on Graphics, 2022
Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images.
Delio Vicini, Sébastien Speierer, Wenzel Jakob   +2 more
semanticscholar   +1 more source

DFR: Differentiable Function Rendering for Learning 3D Generation from Images

Computer graphics forum (Print), 2020
Learning‐based 3D generation is a popular research field in computer graphics. Recently, some works adapted implicit function defined by a neural network to represent 3D objects and have become the current state‐of‐the‐art.
Yunjie Wu, Zhengxing Sun
semanticscholar   +1 more source

Differential Symmetric Functions

Annals of Combinatorics, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Differentiation of Functions

2016
We can now begin the rigorous treatment of calculus in earnest, starting with the notion of a derivative. We can now define derivatives analytically, using limits, in contrast to the geometric definition of derivatives, which uses tangents. The advantage of working analytically is that (a) we do not need to know the axioms of geometry, and (b) these ...
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Forcing and Differentiable Functions

Order, 2011
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The Differentiation of a Composite Function

The Mathematical Gazette, 1971
In a previous issue of the Gazette J. G. Colman gives a formula for the nth derivative of the composite function f[g(x)], states that this is proved by induction and asks for a more direct and illuminating proof.
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On the Composition of Differentiable Functions

Canadian Mathematical Bulletin, 2003
AbstractWe prove that a Banach space X has the Schur property if and only if every X-valued weakly differentiable function is Fréchet differentiable. We give a general result on the Fréchet differentiability of f ○ T, where f is a Lipschitz function and T is a compact linear operator. Finally we study, using in particular a smooth variational principle,
Bachir, Mohammed, Lancien, Gilles
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Functional differentiation in the hippocampus

Hippocampus, 1998
The hippocampus is critically involved in certain kinds of memory. During memory formation, it may operate as an integrated unit, or isolated parts may be responsible for different functions. Recent evidence suggests that the hippocampus is functionally differentiated along its dorsoventral (septotemporal) axis. The cortical and subcortical connections
M B, Moser, E I, Moser
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