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Estimation of density derivatives is a versatile tool in statistical data analysis. A naive approach is to first estimate the density and then compute its derivative. However, such a two-step approach does not work well because a good…

Machine Learning · Statistics 2014-07-01 Hiroaki Sasaki , Yung-Kyun Noh , Masashi Sugiyama

This paper focuses on the equivalent expression of fractional integrals/derivatives with an infinite series. A universal framework for fractional Taylor series is developed by expanding an analytic function at the initial instant or the…

General Mathematics · Mathematics 2022-12-07 Yiheng Wei , YangQuan Chen , Qing Gao , Yong Wang

We present a new quadratic Chabauty method to compute the integral points on certain even degree hyperelliptic curves. Our approach relies on a nontrivial degree zero divisor supported at the two points at infinity to restrict the $p$-adic…

Number Theory · Mathematics 2025-12-01 Stevan Gajović , J. Steffen Müller

D-finite functions and P-recursive sequences are defined in terms of linear differential and recurrence equations with polynomial coefficients. In this paper, we introduce a class of numbers closely related to D-finite functions and…

Number Theory · Mathematics 2018-05-29 Hui Huang , Manuel Kauers

This paper extends the dual calculus with inductive types and coinductive types. The paper first introduces a non-deterministic dual calculus with inductive and coinductive types. Besides the same duality of the original dual calculus, it…

Logic in Computer Science · Computer Science 2015-07-01 Daisuke Kimura , Makoto Tatsuta

In this paper, we propose a new adaptation of the D-iteration algorithm to numerically solve the differential equations. This problem can be reinterpreted in 2D or 3D (or higher dimensions) as a limit of a diffusion process where the…

Numerical Analysis · Computer Science 2012-04-30 Dohy Hong

In this paper we continue the development of the differential calculus started by Aragona-Ferandez-Juriaans. Guided by the topology introduced recently by those authors we introduce the notion of membranes and extend the definition of…

Analysis of PDEs · Mathematics 2008-09-25 J. Aragona , R. Fernandez , S. O. Juriaans , M. Oberguggenberger

Causal functions of sequences occur throughout computer science, from theory to hardware to machine learning. Mealy machines, synchronous digital circuits, signal flow graphs, and recurrent neural networks all have behaviour that can be…

Logic in Computer Science · Computer Science 2019-04-25 David Sprunger , Bart Jacobs

The proper handling of 3D orientations is a central element in many optimization problems in engineering. Unfortunately many researchers and engineers struggle with the formulation of such problems and often fall back to suboptimal…

Differential operators usually result in derivatives expressed as a ratio of differentials. For all but the simplest derivatives, these ratios are typically not algebraically manipulable, but must be held together as a unit in order to…

General Mathematics · Mathematics 2022-10-18 Maria Isabelle Fite , Jonathan Bartlett

The use of neural networks for solving differential equations is practically difficult due to the exponentially increasing runtime of autodifferentiation when computing high-order derivatives. We propose $n$-TangentProp, the natural…

Machine Learning · Computer Science 2024-12-16 Kyle R. Chickering

The paper is devoted to the development of a comprehensive calculus for directional limiting normal cones, subdifferentials and coderivatives in finite dimensions. This calculus encompasses the whole range of the standard generalized…

Optimization and Control · Mathematics 2017-12-14 Matúš Benko , Helmut Gfrerer , Jiří V. Outrata

It is commonly agreed that the success of future proof assistants will rely on their ability to incorporate computations within deduction in order to mimic the mathematician when replacing the proof of a proposition P by the proof of an…

Logic in Computer Science · Computer Science 2007-07-10 Frédéric Blanqui , Jean-Pierre Jouannaud , Pierre-Yves Strub

Although being powerful, the differential transform method yet suffers from a drawback which is how to compute the differential transform of nonlinear non-autonomous functions that can limit its applicability. In order to overcome this…

Classical Analysis and ODEs · Mathematics 2016-12-28 Essam. R. El-Zahar , Abdelhalim Ebaid

We discuss certain aspects of the formal calculus used to describe vertex algebras. In the standard literature on formal calculus, the expression $(x+y)^{n}$, where $n$ is not necessarily a nonnegative integer, is defined as the formal…

Quantum Algebra · Mathematics 2009-12-01 Thomas J. Robinson

Working in point-free topology under the constraints of geometric logic, we prove the Fundamental Theorem of Calculus, and apply it to prove the usual rules for the derivatives of $x^\alpha$, $\gamma^x$, and $\log_\gamma x$.

Category Theory · Mathematics 2023-12-11 Steven Vickers

In this study the general formula for differential and integral operations of fractional calculus via fractal operators by the method of cumulative diminution and cumulative growth is obtained. The under lying mechanism in the success of…

Statistical Mechanics · Physics 2016-08-31 Fevzi Buyukkilic , Zahide Ok Bayrakdar , Dogan Demirhan

This paper presents a self-contained new theory of weak fractional differential calculus in one-dimension. The crux of this new theory is the introduction of a weak fractional derivative notion which is a natural generalization of integer…

Functional Analysis · Mathematics 2020-07-21 Xiaobing Feng , Mitchell Sutton

We introduce the definition of conformable derivative on time scales and develop its calculus. Fundamental properties of the conformable derivative and integral on time scales are proved. Linear conformable differential equations with…

Classical Analysis and ODEs · Mathematics 2018-01-09 Benaoumeur Bayour , Ahmed Hammoudi , Delfim F. M. Torres

As a generalization of Dempster-Shafer theory, D number theory (DNT) aims to provide a framework to deal with uncertain information with non-exclusiveness and incompleteness. Although there are some advances on DNT in previous studies,…

Artificial Intelligence · Computer Science 2020-03-24 Xinyang Deng