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Graph-based models and transforms for signal/data processing with applications to video coding
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Human activity analysis with graph signal processing techniques
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Lifting transforms on graphs: theory and applications
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Dynamic graph analytics for cyber systems security applications
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Exploiting variable task granularities for scalable and efficient parallel graph analytics
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Sampling theory for graph signals with applications to semi-supervised learning
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Network structures: graph theory, statistics, and neuroscience applications
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Learning distributed representations from network data and human navigation
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Learning the geometric structure of high dimensional data using the Tensor Voting Graph
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Physics-aware graph networks for spatiotemporal physical systems
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Compression of signal on graphs with the application to image and video coding
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Representation problems in brain imaging
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Spatiotemporal prediction with deep learning on graphs
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Object representation and magnetic moments in thin alkali films
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Hashcode representations of natural language for relation extraction
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Realistic modeling of wireless communication graphs for the design of efficient sensor network routing protocols
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High throughput computational framework for synthesis and accelerated discovery of dielectric polymer materials using polarizable reactive molecular dynamics and graph neural networks
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Integrating complementary information for photorealistic representation of large-scale environments
Exploiting structure in the Boolean weighted constraint satisfaction problem: a constraint composite graph-based approach
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DBSSC: density-based searchspace-limited subspace clustering
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Feature-preserving simplification and sketch-based creation of 3D models
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Sparse representation models and applications to bioinformatics
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A categorification of the Burau representation via contact geometry
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Reducing inter-component communication vulnerabilities in event-based systems
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Inferring mobility behaviors from trajectory datasets
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