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We provide a simulation algorithm to simulate from a (multivariate) characteristic function, which is only accessible in a black-box format. The method is based on a generative neural network, whose loss function exploits a specific…

Machine Learning · Statistics 2024-09-17 Florian Brück

Roughly speaking, functional analysis is the study of vector spaces of arbitrary dimension over the field of real or complex numbers, and the continuous linear mappings between such spaces. Naturally, the notion of continuity requires a…

Functional Analysis · Mathematics 2025-10-09 Christoph Bock

Color constancy methods often struggle to generalize across different camera sensors due to varying spectral sensitivities. We present GCC, which leverages diffusion models to inpaint color checkers into images for illumination estimation.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Chen-Wei Chang , Cheng-De Fan , Chia-Che Chang , Yi-Chen Lo , Yu-Chee Tseng , Jiun-Long Huang , Yu-Lun Liu

We introduce generative adversarial models in which the discriminator is replaced by a calibrated (non-differentiable) classifier repeatedly enhanced by domain relevant features. The role of the classifier is to prove that the actual and…

Machine Learning · Computer Science 2019-10-08 Shahar Harel , Meir Maor , Amir Ronen

In 1934, Whitney raised the question of how to recognize whether a function f defined on a closed subset X of Euclidean space is the restriction of a function that is continuously differentiable to order p. A necessary and sufficient…

Algebraic Geometry · Mathematics 2007-05-23 E. Bierstone , P. D. Milman , W. Pawlucki

The goal of this expository article is a fairly self-contained account of some averaging processes of functions along sequences of the form $(\alpha^n x)^{}_{n\in\mathbb{N}}$, where $\alpha$ is a fixed real number with $| \alpha | > 1$ and…

Number Theory · Mathematics 2018-01-24 Michael Baake , Alan Haynes , Daniel Lenz

We introduce generalized spatially coupled parallel concatenated codes (GSC-PCCs), a class of spatially coupled turbo-like codes obtained by coupling parallel concatenated codes (PCCs) with a fraction of information bits repeated before the…

Information Theory · Computer Science 2021-05-04 Min Qiu , Xiaowei Wu , Jinhong Yuan , Alexandre Graell i Amat

We consider the application of the generalized Convolution Quadrature (gCQ) to approximate the solution of an important class of sectorial problems. The gCQ is a generalization of Lubich's Convolution Quadrature (CQ) that allows for…

Numerical Analysis · Mathematics 2024-12-05 Jing Guo , Maria Lopez-Fernandez

We introduce the notion of the generalized-analytical function of the poly-number variable, which is a non-trivial generalization of the notion of analytical function of the complex variable and, therefore, may turn out to be fundamental in…

Mathematical Physics · Physics 2007-05-23 G. I. Garasko

This paper studies the approximation of generalized ridge functions, namely of functions which are constant along some submanifolds of $\mathbb{R}^N$. We introduce the notion of linear-sleeve functions, whose function values only depend on…

Numerical Analysis · Mathematics 2017-01-26 Sandra Keiper

Erd\H{o}s \cite{MR168482} proved that the Continuum Hypothesis (CH) is equivalent to the existence of an uncountable family $\mathcal{F}$ of (real or complex) analytic functions, such that $\big\{ f(x) \ : \ f \in \mathcal{F} \big\}$ is…

Logic · Mathematics 2023-06-08 Brent Cody , Sean Cox , Kayla Lee

The main objective of this paper is to look from the unique point of view at some phenomena arising in different areas of probability theory and mathematical statistics. We will try to understand what is common between classical…

Probability · Mathematics 2012-03-01 Oleg Lepski

With the aim of treating the local behaviour of additive functions, we develop analogues of the Matom\"{a}ki-Radziwill theorem that allow us to approximate the average of a general additive function over a typical short interval in terms of…

Number Theory · Mathematics 2021-08-30 Alexander P. Mangerel

Solving the convergence issues of Generative Adversarial Networks (GANs) is one of the most outstanding problems in generative models. In this work, we propose a novel activation function to be used as output of the generator agent. This…

Machine Learning · Computer Science 2023-03-01 Ángel González-Prieto , Alberto Mozo , Sandra Gómez-Canaval , Edgar Talavera

Regression on function spaces is typically limited to models with Gaussian process priors. We introduce the notion of universal functional regression, in which we aim to learn a prior distribution over non-Gaussian function spaces that…

Machine Learning · Computer Science 2024-11-28 Yaozhong Shi , Angela F. Gao , Zachary E. Ross , Kamyar Azizzadenesheli

We study from a physics viewpoint a class of generative neural nets, Gibbs machines, designed for gradual learning. While including variational auto-encoders, they offer a broader universal platform for incrementally adding newly learned…

Computer Vision and Pattern Recognition · Computer Science 2016-07-01 Galin Georgiev

We prove that when individual firms employ constant-returns-to-scale production functions, the aggregate production function defined by the maximum achievable total output given total inputs is always linear on some part of the domain. Our…

Theoretical Economics · Economics 2023-09-28 Christopher P. Chambers , Alexis Akira Toda

We prove that a real x is 1-generic if and only if every differentiable computable function has continuous derivative at x. This provides a counterpart to recent results connecting effective notions of randomness with differentiability. We…

Logic · Mathematics 2014-08-27 Rutger Kuyper , Sebastiaan A. Terwijn

A differential algebra of nonlinear generalized functions is presented as a tool for a wide range of nonsmooth nonlinear problems. The power of the differential algebra is used to do mathematical calculations or proofs; then the final…

Mathematical Physics · Physics 2007-05-23 J. F. Colombeau

While closed timelike curves (CTCs) are not known to exist, studying their consequences has led to nontrivial insights in general relativity, quantum information, and other areas. In this paper we show that if CTCs existed, then quantum…

Quantum Physics · Physics 2009-11-13 Scott Aaronson , John Watrous
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