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02/23/2022
Simulating Network Paths with Recurrent Buffering Units
Simulating physical network paths (e.g., Internet) is a cornerstone rese...
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12/07/2021
A Piece-wise Polynomial Filtering Approach for Graph Neural Networks
Graph Neural Networks (GNNs) exploit signals from node features and the ...
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09/28/2021
IGLU: Efficient GCN Training via Lazy Updates
Graph Convolution Networks (GCN) are used in numerous settings involving...
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07/28/2021
Effective Eigendecomposition based Graph Adaptation for Heterophilic Networks
Graph Neural Networks (GNNs) exhibit excellent performance when graphs h...
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06/24/2021
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs
Graph Neural Networks (GNNs) have shown excellent performance on graphs ...
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02/15/2021
User Embedding based Neighborhood Aggregation Method for Inductive Recommendation
We consider the problem of learning latent features (aka embedding) for ...
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08/19/2020
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
We consider the problem of learning efficient and inductive graph convol...
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04/08/2020
A Graph Convolutional Network Composition Framework for Semi-supervised Classification
Graph convolutional networks (GCNs) have gained popularity due to high p...
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08/01/2016
Learning Semantically Coherent and Reusable Kernels in Convolution Neural Nets for Sentence Classification
The state-of-the-art CNN models give good performance on sentence classi...
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06/26/2012
Predictive Approaches For Gaussian Process Classifier Model Selection
In this paper we consider the problem of Gaussian process classifier (GP...
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06/26/2012
An Additive Model View to Sparse Gaussian Process Classifier Design
We consider the problem of designing a sparse Gaussian process classifie...
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06/26/2012
