
RaWaNet: Enriching Graph Neural Network Input via Random Walks on Graphs
In recent years, graph neural networks (GNNs) have gained increasing pop...
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A lowrank tensor method to reconstruct sparse initial states for PDEs with Isogeometric Analysis
When working with PDEs the reconstruction of a previous state often prov...
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Orientations and matrix functionbased centralities in multiplex network analysis of urban public transport
We study urban public transport systems by means of multiplex networks i...
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Matrix functionbased centrality measures for layercoupled multiplex networks
Centrality measures identify the most important nodes in a complex netwo...
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A Study of GraphBased Approaches for SemiSupervised Time Series Classification
Time series data play an important role in many applications and their a...
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Pseudoinverse Graph Convolutional Networks: Fast Filters Tailored for Large Eigengaps of Dense Graphs and Hypergraphs
Graph Convolutional Networks (GCNs) have proven to be successful tools f...
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Semisupervised Learning for Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix Vector Products
We generalize a graphbased multiclass semisupervised classification te...
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A lowrank matrix equation method for solving PDEconstrained optimization problems
PDEconstrained optimization problems arise in a broad number of applica...
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Efficient Structurepreserving Support Tensor Train Machine
Deploying the multirelational tensor structure of a high dimensional fe...
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A literature survey of matrix methods for data science
Efficient numerical linear algebra is a core ingredient in many applicat...
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Solving differential Riccati equations: A nonlinear spacetime method using tensor trains
Differential algebraic Riccati equations are at the heart of many applic...
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Optimization of a partial differential equation on a complex network
Differential equations on metric graphs can describe many phenomena in t...
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Improved Penalty Algorithm for Mixed Integer PDE Constrained Optimization (MIPDECO) Problems
Optimal control problems including partial differential equation (PDE) a...
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SemiSupervised Classification on NonSparse Graphs Using LowRank Graph Convolutional Networks
Graph Convolutional Networks (GCNs) have proven to be successful tools f...
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Node classification for signed networks using diffuse interface methods
Signed networks are a crucial tool when modeling friend and foe relation...
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NFFT meets Krylov methods: Fast matrixvector products for the graph Laplacian of fully connected networks
The graph Laplacian is a standard tool in data science, machine learning...
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Generalizing diffuse interface methods on graphs: nonsmooth potentials and hypergraphs
Diffuse interface methods have recently been introduced for the task of ...
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Martin Stoll
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