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08/17/2023
Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning
Graph Active Learning (GAL), which aims to find the most informative nod...
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05/30/2023
Contrastive Shapelet Learning for Unsupervised Multivariate Time Series Representation Learning
Recent studies have shown great promise in unsupervised representation l...
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02/24/2023
Inducing Neural Collapse in Deep Long-tailed Learning
Although deep neural networks achieve tremendous success on various clas...
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12/04/2022
Hyperbolic Curvature Graph Neural Network
Hyperbolic space is emerging as a promising learning space for represent...
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11/08/2022
Hyperbolic Graph Representation Learning: A Tutorial
Graph-structured data are widespread in real-world applications, such as...
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04/27/2022
Discovering Representative Attribute-stars via Minimum Description Length
Graphs are a popular data type found in many domains. Numerous technique...
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04/16/2022
TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction
Link prediction is a key problem for network-structured data, attracting...
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02/28/2022
Hyperbolic Graph Neural Networks: A Review of Methods and Applications
Graph neural networks generalize conventional neural networks to graph-s...
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11/30/2021
gCastle: A Python Toolbox for Causal Discovery
is an end-to-end Python toolbox for causal structure learning. It provi...
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11/09/2021
Label-Aware Distribution Calibration for Long-tailed Classification
Real-world data usually present long-tailed distributions. Training on i...
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07/06/2021
An Ensemble Noise-Robust K-fold Cross-Validation Selection Method for Noisy Labels
We consider the problem of training robust and accurate deep neural netw...
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02/08/2021
Mask-GVAE: Blind Denoising Graphs via Partition
We present Mask-GVAE, a variational generative model for blind denoising...
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09/17/2020
Spatio-Temporal Hybrid Graph Convolutional Network for Traffic Forecasting in Telecommunication Networks
Telecommunication networks play a critical role in modern society. With ...
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05/10/2019