Results 121 to 130 of about 4,469 (193)
Hybrid Wasserstein Distance: An Approximation for Optimal Transport Distances
ComputationProjection-based variants of optimal transport, such as the Sliced Wasserstein (SW) and its extensions, have become popular alternatives to classical Wasserstein distances due to their scalability and analytical tractability.
Sara Nassar +2 more
doaj +1 more source
Optimal 1-Wasserstein distance for WGANs
BernoulliThe mathematical forces at work behind Generative Adversarial Networks raise challenging theoretical issues. Motivated by the important question of characterizing the geometrical properties of the generated distributions, we provide a thorough analysis of Wasserstein GANs (WGANs) in both the finite sample and asymptotic regimes.
Stéphanovitch, Arthur +4 more
openaire +4 more sources
A Comparative Review of Specification Tests for Diffusion Models
International Statistical Review, Volume 94, Issue 2, Page 347-381, August 2026.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
Neural‐Initialized Newton: Accelerating Nonlinear Finite Elements via Operator Learning
International Journal for Numerical Methods in Engineering, Volume 127, Issue 14, 30 July 2026.ABSTRACT We propose a Newton‐based scheme, initialized by neural operator predictions, to accelerate the parametric solution of nonlinear problems in computational solid mechanics. First, a physics‐informed neural operator based on conditional neural fields or Fourier neural operators is trained to approximate the nonlinear parametric solution of the ...
Kianoosh Taghikhani +5 more
wiley +1 more source
IEEE AccessMotivation: Accurate prediction of protein subcellular localization (PSL) from sequence is central to cell biology and proteome-scale annotation. However, current approaches face a persistent trade-off: deep learning models often deliver strong accuracy ...
Jiayang Xu, Yangzhou Chen, Xin Chen
doaj +1 more source
Optimal Estimation of Wasserstein Distance on A Tree with An Application to Microbiome Studies. [PDF]
J Am Stat Assoc, 2021 Wang S, Cai TT, Li H.
europepmc +1 more source
Convolutional wasserstein distances
ACM Transactions on Graphics, 2015 This paper introduces a new class of algorithms for optimization problems involving optimal transportation over geometric domains. Our main contribution is to show that optimal transportation can be made tractable over large domains used in graphics, such as images and triangle meshes, improving performance by orders of magnitude compared to previous ...
Solomon, Justin +7 more
openaire +2 more sources
International Journal of Computational Intelligence SystemsThis study evaluates the Wasserstein distance — a metric rooted in optimal transport theory — as a distribution-aware feature input to financial price forecasting and as a dissimilarity input to the Hierarchical Risk Parity (HRP) portfolio construction ...
Insu Choi
doaj +1 more source
A sub-Riemannian model of the motor cortex with Wasserstein distance
Frontiers in Computational NeuroscienceThis study aims to better understand the functional geometry of the motor cortex, starting from different sources of experimental evidence. Recent studies have proved that cells of the primary motor cortex (M1) are sensitive to short hand trajectories ...
Jawad Ali +2 more
doaj +1 more source
Quantum distance approximation for persistence diagrams
Journal of Physics: ComplexityTopological data analysis (TDA) methods can be useful for classification and clustering tasks in many different fields as they can provide two dimensional persistence diagrams that summarize important information about the shape of potentially complex ...
Bernardo Ameneyro +3 more
doaj +1 more source