paper-with-me

홈 › Papers

Nowhere coexpanding functions

2023-03-22 · Andrew Cook, Andy Hammerlindl, Warwick Tucker

We define a family of $C^1$ functions which we call "nowhere coexpanding functions" that is closed under composition and includes all $C^3$ functions with non-positive Schwarzian derivative. We establish results on the number and nature of the fixed points of these functions, including a generalisation of a classic result of Singer.

📄 PDF Abstract BibTeX arXiv:2303.12814

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

Sigmoid Activation 설명 없음

Similar Papers 제목 키워드 기반

Neural Network Approximation of Refinable Functions

2021-07-28 · Ingrid Daubechies, Ronald DeVore, Nadav Dym, Shira Faigenbaum-Golovin 외

In the desire to quantify the success of neural networks in deep learning and other applications, there is a great interest in understanding which functions are efficiently approximated by the outputs of neural networks.…

The universal approximation power of finite-width deep ReLU networks

2018-06-05 · ICLR 2019 5 · Dmytro Perekrestenko, Philipp Grohs, Dennis Elbrächter, Helmut Bölcskei

We show that finite-width deep ReLU neural networks yield rate-distortion optimal approximation (B\"olcskei et al., 2018) of polynomials, windowed sinusoidal functions, one-dimensional oscillatory textures, and the Weier…

On the algebra of Koopman eigenfunctions and on some of their infinities

2026-04-23 · Zahra Monfared, Saksham Malhotra, Sekiya Hajime, Ioannis Kevrekidis 외 arxiv

For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a multiplicative group. Here, we exploit this property to accelerate the…

Universal Approximation with Deep Narrow Networks

2019-05-21 · Patrick Kidger, Terry Lyons

The classical Universal Approximation Theorem holds for neural networks of arbitrary width and bounded depth. Here we consider the natural `dual' scenario for networks of bounded width and arbitrary depth. Precisely, let…

Shortcuts Everywhere and Nowhere: Exploring Multi-Trigger Backdoor Attacks

2024-01-27 · Yige Li, Jiabo He, Hanxun Huang, Jun Sun 외

Backdoor attacks have become a significant threat to the pre-training and deployment of deep neural networks (DNNs). Although numerous methods for detecting and mitigating backdoor attacks have been proposed, most rely o…