Results 31 to 40 of about 33,205 (174)

Graded persistence diagrams and persistence landscapes

open access: yes, 2021
We introduce a refinement of the persistence diagram, the graded persistence diagram. It is the Mobius inversion of the graded rank function, which is obtained from the rank function using the unary numeral system.
Betthauser, Leo   +2 more
core  

Matricial Wasserstein-1 Distance

open access: yes, 2017
In this note, we propose an extension of the Wasserstein 1-metric ($W_1$) for matrix probability densities, matrix-valued density measures, and an unbalanced interpretation of mass transport. The key is using duality theory, in particular, a "dual of the
Chen, Yongxin   +3 more
core   +1 more source

Scalar conservation laws seen as gradient flows: known results and new perspectives

open access: yesESAIM: Proceedings and Surveys, 2016
We review some results in the literature which attempted (only partly successfully) at linking the theory of scalar conservation laws with the Wasserstein gradient flow theory.
Di Francesco Marco
doaj   +1 more source

The Gromov–Wasserstein Distance: A Brief Overview

open access: yesAxioms, 2014
We recall the construction of the Gromov–Wasserstein distance and concentrate on quantitative aspects of the definition.
Facundo Mémoli
doaj   +1 more source

Wasserstein Distance Guided Representation Learning for Domain Adaptation

open access: yes, 2018
Domain adaptation aims at generalizing a high-performance learner on a target domain via utilizing the knowledge distilled from a source domain which has a different but related data distribution.
Qu, Yanru   +3 more
core   +1 more source

Towards Inverse Modeling of Landscapes Using the Wasserstein Distance

open access: yesGeophysical Research Letters, 2023
Extricating histories of uplift and erosion from landscapes is crucial for many branches of the Earth sciences. An objective way to calculate such histories is to identify calibrated models that minimize misfit between observations (e.g., topography) and
M. J. Morris, A. G. Lipp, G. G. Roberts
doaj   +1 more source

Basic statistics for probabilistic symbolic variables: a novel metric-based approach

open access: yes, 2013
In data mining, it is usually to describe a set of individuals using some summaries (means, standard deviations, histograms, confidence intervals) that generalize individual descriptions into a typology description. In this case, data can be described by
Irpino, Antonio, Verde, Rosanna
core   +1 more source

A High‐Throughput Live Imaging Platform to Investigate Circuit‐Dependent Regulation of Circadian Rhythms in Brain Tissue

open access: yesAdvanced Science, EarlyView.
Biological rhythms coordinate physiology, from genes to behavior. Study of circadian rhythms in brain tissue is constrained by limited throughput and spatial and temporal information quality. A new platform for high‐throughput, long‐term multiplexed fluorescent live imaging of circadian rhythms in brain slices is introduced.
Marco Ferrari   +3 more
wiley   +1 more source

High-Dimensional Distributionally Robust Mean-Variance Efficient Portfolio Selection

open access: yesMathematics, 2023
This paper introduces a novel distributionally robust mean-variance portfolio estimator based on the projection robust Wasserstein (PRW) distance. This approach addresses the issue of increasing conservatism of portfolio allocation strategies due to high-
Zhonghui Zhang, Huarui Jing, Chihwa Kao
doaj   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

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