Results 51 to 60 of about 4,387 (252)
EEG Multi-Mode Oscillatory Brain State Allocation Using Switching Spectral Gaussian Processes
IEEE AccessWe propose a new model for the non-stationary brain state allocation problem from electroencephalography (EEG) data, based on spectral features and their interaction.
Yunier Prieur-Coloma +3 more
doaj +1 more source
Remote Sensing, 2018 In this paper, we introduce a novel classification framework for hyperspectral images (HSIs) by jointly employing spectral, spatial, and hierarchical structure information.
Yi Wang, Hexiang Duan
doaj +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Advanced Intelligent Discovery, EarlyView.Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Flexible Graph Comparison Using HMMs
IEEE AccessGraphs are powerful means for representing structured data. Graph comparison is consequently an important tool for decision support and several techniques have therefore been proposed for comparing two graphs, including Substructure-based techniques ...
Mohammad Mourad Abdoulahi, Sylvain Iloga
doaj +1 more source
Advanced Intelligent Systems, EarlyView.Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
HEAT KERNEL INTEREST RATE MODELS WITH TIME-INHOMOGENEOUS MARKOV PROCESSES [PDF]
International Journal of Theoretical and Applied Finance, 2012 We consider a heat kernel approach for the development of stochastic pricing kernels. The kernels are constructed by positive propagators, which are driven by time-inhomogeneous Markov processes. We multiply such a propagator with a positive, time-dependent and decreasing weight function, and integrate the product over time.
Jiro Akahori, Andrea Macrina
openaire +4 more sources
Advanced Intelligent Systems, EarlyView.This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models
Applied Stochastic Models in Business and Industry, EarlyView.ABSTRACT Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs.
Mariflor Vega Carrasco +4 more
wiley +1 more source
Markov Blanket Ranking Using Kernel-Based Conditional Dependence Measures [PDF]
, 2019 10 pages, 4 figures, 2 algorithms, NIPS 2013 Workshop on Causality, code: github.com/ericstrobl/
Strobl, Eric V., Visweswaran, Shyam
openaire +2 more sources
Duality and intertwining for discrete Markov kernels: relations and examples [PDF]
Advances in Applied Probability, 2011 We supply some relations that establish intertwining from duality and give a probabilistic interpretation. This is carried out in the context of discrete Markov chains, fixing up the background of previous relations established for monotone chains and their Siegmund duals. We revisit the duality for birth-and-death chains and the nonneutral Moran model,
Huillet, Thierry, Martinez, Servet
openaire +5 more sources