Results 91 to 100 of about 32,144 (182)
A Comparative Review of Specification Tests for Diffusion Models
International Statistical Review, EarlyView.Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez +3 more
wiley +1 more source
Geometrical aspects of entropy production in stochastic thermodynamics based on Wasserstein distance
Physical Review Research, 2021 We study a relationship between optimal transport theory and stochastic thermodynamics for the Fokker-Planck equation. We show that the lower bound on the entropy production is the action measured by the path length of the L^{2}-Wasserstein distance ...
Muka Nakazato, Sosuke Ito
doaj +1 more source
Subspace Robust Wasserstein Distances
, 2019 Making sense of Wasserstein distances between discrete measures in high-dimensional settings remains a challenge. Recent work has advocated a two-step approach to improve robustness and facilitate the computation of optimal transport, using for instance projections on random real lines, or a preliminary quantization of the measures to reduce the size ...
Paty, François-Pierre, Cuturi, Marco
openaire +2 more sources
Intrinsic Dimension Estimation Using Wasserstein Distances
, 2021 It has long been thought that high-dimensional data encountered in many practical machine learning tasks have low-dimensional structure, i.e., the manifold hypothesis holds. A natural question, thus, is to estimate the intrinsic dimension of a given population distribution from a finite sample.
Block, Adam +3 more
openaire +3 more sources
On a general matrix-valued unbalanced optimal transport problem
European Journal of Applied MathematicsWe introduce a general class of transport distances $\mathrm {WB}_{\Lambda }$ over the space of positive semi-definite matrix-valued Radon measures $\mathcal {M}(\Omega, \mathbb {S}_+^n)$ , called the weighted Wasserstein–Bures distance ...
Bowen Li, Jun Zou
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Stability of the global attractor under Markov-Wasserstein noise [PDF]
, 2011 We develop a "weak Wa\.zewski principle" for discrete and continuous time dynamical systems on metric spaces having a weaker topology to show that attractors can be continued in a weak sense.
Kell, Martin
core
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
International Statistical Review, EarlyView.Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
Generalized Sliced Wasserstein Distances
, 2019 The Wasserstein distance and its variations, e.g., the sliced-Wasserstein (SW) distance, have recently drawn attention from the machine learning community. The SW distance, specifically, was shown to have similar properties to the Wasserstein distance, while being much simpler to compute, and is therefore used in various applications including ...
Kolouri, Soheil +4 more
openaire +2 more sources
Density‐Valued ARMA Models by Spline Mixtures
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper proposes a novel framework for modeling time series of probability density functions by extending autoregressive moving average (ARMA) models to density‐valued data. The method is based on a transformation approach, wherein each density function on a compact domain [0,1]d$$ {\left[0,1\right]}^d $$ is approximated by a B‐spline ...
Yasumasa Matsuda, Rei Iwafuchi
wiley +1 more source
Critical scaling of the quantum Wasserstein distance
Physical Review ResearchDistinguishing quantum states with minimal sampling overhead is of fundamental importance to teach quantum data to an algorithm. Recently, the quantum Wasserstein distance emerged from the theory of quantum optimal transport as a promising tool in this ...
Gonzalo Camacho, Benedikt Fauseweh
doaj +1 more source