Results 31 to 40 of about 3,027 (198)
Robust Multivehicle Tracking With Wasserstein Association Metric in Surveillance Videos
IEEE Access, 2020 Vehicle tracking based on surveillance videos is of great significance in the highway traffic monitoring field. In real-world vehicle-tracking applications, partial occlusion and objects with similarly appearing distractors pose significant challenges ...
Yanjie Zeng +5 more
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Tellus: Series B, Chemical and Physical Meteorology, 2016 The verification of simulations against data and the comparison of model simulation of pollutant fields rely on the critical choice of statistical indicators. Most of the scores are based on point-wise, that is, local, value comparison.
Alban Farchi +4 more
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Homogenisation of Wasserstein gradient flows
European Journal of Applied MathematicsWe prove the convergence of a Wasserstein gradient flow of a free energy in inhomogeneous media. Both the energy and media can depend on the spatial variable in a fast oscillatory manner.
Yuan Gao, Nung Kwan Yip
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Estimation of the drift parameter for the fractional stochastic heat equation via power variation
Modern Stochastics: Theory and Applications, 2019 We define power variation estimators for the drift parameter of the stochastic heat equation with the fractional Laplacian and an additive Gaussian noise which is white in time and white or correlated in space.
Zeina Mahdi Khalil, Ciprian Tudor
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Mapper Comparison with Wasserstein Metrics
CoRR, 2018 The challenge of describing model drift is an open question in unsupervised learning. It can be difficult to evaluate at what point an unsupervised model has deviated beyond what would be expected from a different sample from the same population. This is particularly true for models without a probabilistic interpretation. One such family of techniques,
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Distribution’s template estimate with Wasserstein metrics
Bernoulli, 2015 In this paper we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution.
Boissard, Emmanuel +2 more
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Frontiers in PharmacologyBackgroundPopulation pharmacokinetic modeling relies on adequate covariate specification to explain interindividual variability and support model-informed precision dosing.
Nicolas Simon +3 more
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Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
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Energies, 2022 This paper proposes a distributed robust multi-energy dynamic optimal power flow (DR-DOPF) model to overcome the uncertainty of new energy outputs and to reduce water spillage in hydropower plants.
Gengli Song, Hua Wei
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