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08/22/2023
Graph Encoding and Neural Network Approaches for Volleyball Analytics: From Game Outcome to Individual Play Predictions
This research aims to improve the accuracy of complex volleyball predict...
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05/25/2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization
Explaining the decisions made by machine learning models for high-stakes...
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05/23/2023
Link Prediction without Graph Neural Networks
Link prediction, which consists of predicting edges based on graph featu...
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02/01/2023
Learning Prototype Classifiers for Long-Tailed Recognition
The problem of long-tailed recognition (LTR) has received attention in r...
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10/21/2022
Global Counterfactual Explainer for Graph Neural Networks
Graph neural networks (GNNs) find applications in various domains such a...
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05/23/2022
Deep Representations for Time-varying Brain Datasets
Finding an appropriate representation of dynamic activities in the brain...
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03/15/2022
Incorporating Heterophily into Graph Neural Networks for Graph Classification
Graph neural networks (GNNs) often assume strong homophily in graphs, se...
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01/24/2022
Graph Neural Diffusion Networks for Semi-supervised Learning
Graph Convolutional Networks (GCN) is a pioneering model for graph-based...
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10/24/2021
A Broader Picture of Random-walk Based Graph Embedding
Graph embedding based on random-walks supports effective solutions for m...
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10/23/2021
Event Detection on Dynamic Graphs
Event detection is a critical task for timely decision-making in graph a...
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10/17/2021
POLE: Polarized Embedding for Signed Networks
From the 2016 U.S. presidential election to the 2021 Capitol riots to th...
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04/05/2020
DeepMap: Learning Deep Representations for Graph Classification
Graph-structured data arise in many scenarios. A fundamental problem is ...
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03/24/2020
Incorporating User's Preference into Attributed Graph Clustering
Graph clustering has been studied extensively on both plain graphs and a...
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02/23/2020
Tree++: Truncated Tree Based Graph Kernels
Graph-structured data arise ubiquitously in many application domains. A ...
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03/08/2019
Learning Heuristics over Large Graphs via Deep Reinforcement Learning
In this paper, we propose a deep reinforcement learning framework called...
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01/08/2019
K-Core Minimization: A Game Theoretic Approach
K-cores are maximal induced subgraphs where all vertices have degree at ...
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09/30/2016
Outlier Detection from Network Data with Subnetwork Interpretation
Detecting a small number of outliers from a set of data observations is ...
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10/17/2015