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Related papers: Introduction to rough paths theory

200 papers

The recent progresses in Machine Learning opened the door to actual applications of learning algorithms but also to new research directions both in the field of Machine Learning directly and, at the edges with other disciplines. The case…

Disordered Systems and Neural Networks · Physics 2023-07-17 Aurélien Decelle

Following the approach and the terminology introduced in [A. Deya and R. Schott, On the rough paths approach to non-commutative stochastic calculus, J. Funct. Anal., 2013], we construct a product L{\'e}vy area above the $q$-Brownian motion…

Probability · Mathematics 2020-12-09 Aurélien Deya , René Schott

These are the notes for a set of lectures delivered by the two authors at the Les Houches Summer School on `Complex Systems' in July 2006. They provide an introduction to the basic concepts in modern (probabilistic) coding theory,…

Information Theory · Computer Science 2007-07-13 Andrea Montanari , Rudiger Urbanke

This paper is an extended and reworked version of a short course given by the author at ''Uzbekistan-Ukrainian readings in stochastic processes'', Tashkent-Kyiv, 2022, and was prepared for a special issue of ''Theory of stochastic…

Probability · Mathematics 2024-04-03 M. B. Vovchanskyi

The problem at the heart of this tutorial consists in modeling the path choice behavior of network users. This problem has been extensively studied in transportation science, where it is known as the route choice problem. In this…

Machine Learning · Statistics 2022-06-10 Maëlle Zimmermann , Emma Frejinger

In problem solving, understanding the problem that one seeks to solve is an essential initial step. In this paper, we propose computational methods for facilitating problem understanding through the task of recognizing the unknown in…

Computation and Language · Computer Science 2021-11-30 Ndapa Nakashole

We extend the validity of a simple method for the existence of a density for stochastic differential equations, first introduced in [DebRom2014], by proving local estimate for the density, existence for the density with summable drift, and…

Probability · Mathematics 2017-10-13 Marco Romito

Transport phenomena are ubiquitous in nature and known to be important for various scientific domains. Examples can be found in physics, electrochemistry, heterogeneous catalysis, physiology, etc. To obtain new information about diffusive…

Probability · Mathematics 2007-05-23 Denis S. Grebenkov

These are expanded notes for the mini-course given by the author at the 2022 ICTS workshop `Elliptic curves and the special values of $L$-functions'.

Number Theory · Mathematics 2024-04-22 Francesc Castella

We give a stochastic generalization of transport theorem on smooth manifold. Furthermore, we deduce a system of continuity equation and present some application on torus.

Probability · Mathematics 2015-05-11 Pedro Catuogno , Simão N. Stelmastchuk

We develop a general framework for pathwise stochastic integration that extends F\"ollmer's classical approach beyond gradient-type integrands and standard left-point Riemann sums and provides pathwise counterparts of It\^o, Stratonovich,…

Probability · Mathematics 2025-07-24 Purba Das , Anna P. Kwossek , David J. Prömel

Recently a path integral formalism has been proposed by the author which gives the time evolution of moments of slow variables in a Hamiltonian statistical system. This closure relies on evaluating the informational discrepancy of a time…

Mathematical Physics · Physics 2015-10-23 Richard Kleeman

These lecture notes provide an introduction to Langevin processes and briefly discuss some interesting properties and simple applications. They compile material presented at the "School of Physics and Mathematics Without Frontiers"…

Statistical Mechanics · Physics 2025-04-17 Leticia F. Cugliandolo

We present here a general framework and a specific algorithm for predicting the destination, route, or more generally a pattern, of an ongoing journey, building on the recent work of [Y. Lassoued, J. Monteil, Y. Gu, G. Russo, R. Shorten,…

Machine Learning · Computer Science 2018-09-03 Jonathan P. Epperlein , Julien Monteil , Mingming Liu , Yingqi Gu , Sergiy Zhuk , Robert Shorten

These notes contain a survey of some aspects of the theory of graded differential algebras and of noncommutative differential calculi as well as of some applications connected with physics. They also give a description of several new…

Quantum Algebra · Mathematics 2007-05-23 Michel Dubois-Violette

Deep learning algorithms have made incredible strides in the past decade, yet due to their complexity, the science of deep learning remains in its early stages. Being an experimentally driven field, it is natural to seek a theory of deep…

Machine Learning · Statistics 2025-04-18 Zohar Ringel , Noa Rubin , Edo Mor , Moritz Helias , Inbar Seroussi

The path probability of a particle undergoing stochastic motion is studied by the use of functional technique, and the general formula is derived for the path probability distribution functional. The probability of finding paths inside a…

Statistical Mechanics · Physics 2016-02-16 Masayuki Hattori , Sumiyoshi Abe

The original Donsker theorem says that a standard random walk converges in distribution to a Brownian motion in the space of continuous functions. It has recently been extended to enriched random walks and enriched Brownian motion. We use…

Probability · Mathematics 2018-06-18 Laure Coutin , Laurent Decreusefond

We derive an invariance principle for the lift to the rough path topology of stochastic processes with delayed regenerative increments under an optimal moment condition. An interesting feature of the result is the emergence of area anomaly,…

Probability · Mathematics 2021-01-14 Tal Orenshtein

In this paper, we describe two effects of the L\'evy area correction on the invariant measure of stochastic rigid body dynamics on geometric rough paths. From the viewpoint of dynamics, the L\'evy area correction introduces an additional…

Chaotic Dynamics · Physics 2023-06-21 Theo Diamantakis , Darryl D. Holm , Grigorios A. Pavliotis