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05/29/2023
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs
This paper studies the relationship between a graph neural network (GNN)...
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03/20/2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back
In this work we introduce a convolution operation over the tangent bundl...
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12/15/2022
Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs
In this paper we propose a pooling approach for convolutional informatio...
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11/20/2022
Convolutional Filtering on Sampled Manifolds
The increasing availability of geometric data has motivated the need for...
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10/26/2022
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back
In this work we introduce a convolution operation over the tangent bundl...
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10/01/2022
Convolutional Neural Networks on Manifolds: From Graphs and Back
Geometric deep learning has gained much attention in recent years due to...
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07/08/2022
Stability of Aggregation Graph Neural Networks
In this paper we study the stability properties of aggregation graph neu...
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10/10/2021
Stability of Neural Networks on Manifolds to Relative Perturbations
Graph Neural Networks (GNNs) show impressive performance in many practic...
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06/07/2021
Stability of Manifold Neural Networks to Deformations
Stability is an important property of graph neural networks (GNNs) which...
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11/05/2020
Unsupervised Learning for Asynchronous Resource Allocation in Ad-hoc Wireless Networks
We consider optimal resource allocation problems under asynchronous wire...
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10/23/2020
Graph and graphon neural network stability
Graph neural networks (GNNs) are learning architectures that rely on kno...
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06/09/2020
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints
Phase I dose-finding trials are increasingly challenging as the relation...
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02/22/2018