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We investigate the use of path signatures in a machine learning context for hedging exotic derivatives under non-Markovian stochastic volatility models. In a deep learning setting, we use signatures as features in feedforward neural…

Machine Learning · Statistics 2025-08-12 Eduardo Abi Jaber , Louis-Amand Gérard

It has been shown recently that graph signals with small total variation can be accurately recovered from only few samples if the sampling set satisfies a certain condition, referred to as the network nullspace property. Based on this…

Machine Learning · Statistics 2017-04-18 Saeed Basirian , Alexander Jung

This paper considers a random structure on the lattice $\mathbb{Z}^2$ of the following kind. To each edge $e$ a random variable $X_e$ is assigned, together with a random sign $Y_e \in \{-1,+1\}$. For an infinite self-avoiding path on…

Probability · Mathematics 2019-07-24 Emilio De Santis , Mauro Piccioni

A communication network can be modeled as a directed connected graph with edge weights that characterize performance metrics such as loss and delay. Network tomography aims to infer these edge weights from their pathwise versions measured…

Optimization and Control · Mathematics 2019-08-12 Mahmood Ettehad , Nick Duffield , Gregory Berkolaiko

This paper is concerned with the general theme of relating the Large Deviation Principle (LDP) for the invariant measures of stochastic processes to the associated sample path LDP. It is shown that if the sample path deviation function…

Probability · Mathematics 2023-08-10 Anatolii A. Puhalskii

This paper develops a structural theory of unique shortest paths in real-weighted graphs. Our main goal is to characterize exactly which sets of node sequences, which we call path systems, can be realized as unique shortest paths in a graph…

Data Structures and Algorithms · Computer Science 2018-10-18 Greg Bodwin

This paper concerns a random walk that moves on the integer lattice and has zero mean and a finite variance. We obtain first an asymptotic estimate of the transition probability of the walk absorbed at the origin, and then, using the…

Probability · Mathematics 2011-03-31 Kohei Uchiyama

The sequential data observed in earth science can be regarded as paths in multidimensional space. To read the path effectively, it is useful to convert it into a sequence of numbers called the signature, which can faithfully describe the…

Geophysics · Physics 2022-04-05 Nozomi Sugiura

A random walk with counterbalanced steps is a process of partial sums $\check S(n)=\check X_1+ \cdots + \check X_n$ whose steps $\check X_n$ are given recursively as follows. For each $n\geq 2$, with a fixed probability $p$, $\check X_n$ is…

Probability · Mathematics 2022-07-05 Jean Bertoin

Random walks play an important role in probing the structure of complex networks. On traditional networks, they can be used to extract community structure, understand node centrality, perform link prediction, or capture the similarity…

Physics and Society · Physics 2024-06-13 Shazia'Ayn Babul , Yu Tian , Renaud Lambiotte

In the simple case of a Bernoulli shift on two symbols, zero and one, by permuting the symbols, it is obvious that any two equal entropy shifts are isomorphic. We show that the isomorphism can be realized by a factor that maps a binary…

Dynamical Systems · Mathematics 2016-02-16 Terry Soo

In the last decade, the concept of path signature has achieved significant success in data science applications. It offers a powerful set of features that effectively capture and describe the characteristics of paths or sequential data.…

Rings and Algebras · Mathematics 2025-01-13 Ilya Chevyrev , Joscha Diehl , Kurusch Ebrahimi-Fard , Nikolas Tapia

The paper considers the behaviour of the number of paths of length $N$ on graphs with two heavy roots. Such vertices can be entropic traps. Numerical analysis is carried out for graphs with different degrees of root vertices. In the…

Statistical Mechanics · Physics 2023-02-14 Z. D. Matyushina

We bring a control perspective to the problem of identifying paths of measures for sampling via dynamic measure transport (DMT). We highlight the fact that commonly used paths may be poor choices for DMT and connect existing methods for…

Machine Learning · Statistics 2025-11-07 Aimee Maurais , Bamdad Hosseini , Youssef Marzouk

We count the number of lattice paths lying under a cyclically shifting piecewise linear boundary of varying slope. Our main result extends well known enumerative formulae concerning lattice paths, and its derivation involves a classical…

Combinatorics · Mathematics 2007-12-20 J. Irving , A. Rattan

We investigate path integral formalism for continuum theory. It is shown that the path integral for the soft modes can be represented in the form of a lattice theory. Kinetic term of this lattice theory has a standard form and potential…

High Energy Physics - Lattice · Physics 2007-05-23 V. M. Belyaev

We develop a consistent method for estimating the parameters of a rich class of path-dependent SDEs, called signature SDEs, which can model general path-dependent phenomena. Path signatures are iterated integrals of a given path with the…

Statistics Theory · Mathematics 2025-05-29 Pardis Semnani , Vincent Guan , Elina Robeva , Darrick Lee

We consider the motion of a particle on a Galton Watson tree, when the probabilities of jumping from a vertex to any one of its neighbours is determined by a random process. Given the tree, positive weights are assigned to the edges in such…

Probability · Mathematics 2016-05-02 A. D. Barbour , A. Collevecchio

The theory of sampling and recovery of bandlimited graph signals has been extensively studied. However, in many cases, the observation of a signal is quite coarse. For example, users only provide simple comments such as "like" or "dislike"…

Signal Processing · Electrical Eng. & Systems 2024-02-20 Wenwei Liu , Hui Feng , Feng Ji , Bo Hu

The aim of the presented research is to give a rigorous mathematical approach to Feynman path integrals based on strong (pathwise) approximations based on simple random walks.

Mathematical Physics · Physics 2018-03-22 Tamás Szabados
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