Graph Signal Processing for Compositional Data
The field of graph signal processing (GSP) offers numerous methodologies for handling data whose domain is captured by graphs. In this work, we introduce novel GSP concepts that are tailored to compositional data, a type of data that represents parts of ...
Matz, Gerald; orcid: +1 more
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Adaptive graph signal processing for robust multimodal fusion with dynamic semantic alignment. [PDF]
Karthikeya KV +4 more
europepmc +1 more source
Graph-based analysis of frequency response measurements for assessment of winding faults in power autotransformers. [PDF]
Azad VT +3 more
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Untamed: Unconstrained Tensor Decomposition and Graph Node Embedding for Cortical Parcellation. [PDF]
Liu Y, Li J, Wisnowski JL, Leahy RM.
europepmc +1 more source
Toward leveraging intrinsic point cloud features in 3D adversarial attacks. [PDF]
Naderi H, Dinesh C, Bajić IV, Kasaei S.
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Smart Logistics Model for Supply Chain Management via Brain-Inspired Geometric Deep Networks. [PDF]
Khaleghi M +5 more
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Spectral Properties of Complex Distributed Intelligence Systems Coupled with an Environment. [PDF]
Alodjants AP +3 more
europepmc +1 more source
Graph Laplacian Learning with Exponential Family Noise. [PDF]
Shi C, Mishne G.
europepmc +1 more source
Exploring Neurofunctional Phase Transition Patterns in Autism Spectrum Disorder via Thermodynamics Parameters. [PDF]
Qin D, Chen Y, Kuruoglu EE.
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Continuous Emotion Recognition Using EDA-Graphs: A Graph Signal Processing Approach for Affective Dimension Estimation. [PDF]
Mercado-Diaz LR +3 more
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