Convergence to Equilibrium in Wasserstein Distance for Damped Euler Equations with Interaction Forces
Sign Up to like & getrecommendations! Published in 2017 at "Communications in Mathematical Physics"
DOI: 10.1007/s00220-018-3276-8
Abstract: We develop tools to construct Lyapunov functionals on the space of probability measures in order to investigate the convergence to global equilibrium of a damped Euler system under the influence of external and interaction potential… read more here.
Keywords: distance; equilibrium; interaction; damped euler ... See more keywords
Data-driven Stochastic Programming with Distributionally Robust Constraints Under Wasserstein Distance: Asymptotic Properties
Sign Up to like & getrecommendations! Published in 2020 at "Journal of the Operations Research Society of China"
DOI: 10.1007/s40305-020-00313-w
Abstract: Distributionally robust optimization is a dominant paradigm for decision-making problems where the distribution of random variables is unknown. We investigate a distributionally robust optimization problem with ambiguities in the objective function and countably infinite constraints.… read more here.
Keywords: distributionally robust; data driven; optimization; problem ... See more keywords
Classification of atomic environments via the Gromov–Wasserstein distance
Sign Up to like & getrecommendations! Published in 2021 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2020.110144
Abstract: Interpreting molecular dynamics simulations usually involves automated classification of local atomic environments to identify regions of interest. Existing approaches are generally limited to a small number of reference structures and only include limited information about… read more here.
Keywords: wasserstein distance; classification; atomic environments; gromov wasserstein ... See more keywords
Topological data assimilation using Wasserstein distance
Sign Up to like & getrecommendations! Published in 2018 at "Inverse Problems"
DOI: 10.1088/1361-6420/aae993
Abstract: This work combines a level-set approach and the optimal transport-based Wasserstein distance in a data assimilation framework. The primary motivation of this work is to reduce assimilation artifacts resulting from the position and observation error… read more here.
Keywords: using wasserstein; topological data; distance; data assimilation ... See more keywords
The Quantum Wasserstein Distance of Order 1
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2021.3076442
Abstract: We propose a generalization of the Wasserstein distance of order 1 to the quantum states of $n$ qudits. The proposal recovers the Hamming distance for the vectors of the canonical basis, and more generally the… read more here.
Keywords: proposed distance; distance; distance order; wasserstein distance ... See more keywords
Aggregated Wasserstein Distance and State Registration for Hidden Markov Models
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2019.2908635
Abstract: We propose a framework, named Aggregated Wasserstein, for computing a dissimilarity measure or distance between two Hidden Markov Models with state conditional distributions being Gaussian. For such HMMs, the marginal distribution at any time position… read more here.
Keywords: hidden markov; distance; wasserstein distance; markov models ... See more keywords
A Linear Programming Approximation of Distributionally Robust Chance-Constrained Dispatch With Wasserstein Distance
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Power Systems"
DOI: 10.1109/tpwrs.2020.2978934
Abstract: This paper proposes a data-driven distributionally robust chance constrained real-time dispatch (DRCC-RTD) considering renewable generation forecasting errors. The proposed DRCC-RTD model minimizes the expected quadratic cost function and guarantees that the two-sided chance constraints are… read more here.
Keywords: wasserstein distance; linear programming; chance; distributionally robust ... See more keywords
The back-and-forth method for the quadratic Wasserstein distance-based full-waveform inversion
Sign Up to like & getrecommendations! Published in 2023 at "GEOPHYSICS"
DOI: 10.1190/geo2022-0383.1
Abstract: The conventional least-squares misfit function compares the synthetic data to the observed data in a point by point style. The Wasserstein distance function, also called optimal transport function, matches patterns. The kinematic information of a… read more here.
Keywords: function; full waveform; wasserstein; wasserstein distance ... See more keywords
Hybrid Wasserstein distance and fast distribution clustering
Sign Up to like & getrecommendations! Published in 2019 at "Electronic Journal of Statistics"
DOI: 10.1214/19-ejs1639
Abstract: We define a modified Wasserstein distance for distribution clustering which inherits many of the properties of the Wasserstein distance but which can be estimated easily and computed quickly. The modified distance is the sum of… read more here.
Keywords: hybrid wasserstein; distance; distribution clustering; distance fast ... See more keywords
Probability Forecast Combination via Entropy Regularized Wasserstein Distance
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DOI: 10.21799/frbp.wp.2020.31
Abstract: We propose probability and density forecast combination methods that are defined using the entropy regularized Wasserstein distance. First, we provide a theoretical characterization of the combined density forecast based on the regularized Wasserstein distance under… read more here.
Keywords: entropy; density; regularized wasserstein; forecast ... See more keywords
Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance
Sign Up to like & getrecommendations! Published in 2019 at "Bernoulli"
DOI: 10.3150/18-bej1065
Abstract: The Wasserstein distance between two probability measures on a metric space is a measure of closeness with applications in statistics, probability, and machine learning. In this work, we consider the fundamental question of how quickly… read more here.
Keywords: finite sample; sharp asymptotic; asymptotic finite; rates convergence ... See more keywords