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09/02/2023
Pure Message Passing Can Estimate Common Neighbor for Link Prediction
Message Passing Neural Networks (MPNNs) have emerged as the de facto sta...
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05/31/2023
Information Fusion via Symbolic Regression: A Tutorial in the Context of Human Health
This tutorial paper provides a general overview of symbolic regression (...
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05/27/2023
What indeed can GPT models do in chemistry? A comprehensive benchmark on eight tasks
Large Language Models (LLMs) with strong abilities in natural language p...
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04/12/2023
Towards Understanding How Data Augmentation Works with Imbalanced Data
Data augmentation forms the cornerstone of many modern machine learning ...
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04/09/2023
Class-Imbalanced Learning on Graphs: A Survey
The rapid advancement in data-driven research has increased the demand f...
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02/01/2023
Knowledge Distillation on Graphs: A Survey
Graph Neural Networks (GNNs) have attracted tremendous attention by demo...
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12/15/2022
Interpretable ML for Imbalanced Data
Deep learning models are being increasingly applied to imbalanced data i...
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11/29/2022
FakeEdge: Alleviate Dataset Shift in Link Prediction
Link prediction is a crucial problem in graph-structured data. Due to th...
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08/22/2022
NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs
While Graph Neural Networks (GNNs) have demonstrated their efficacy in d...
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08/21/2022
Heterogeneous Graph Masked Autoencoders
Generative self-supervised learning (SSL), especially masked autoencoder...
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07/08/2022
Graph-based Molecular Representation Learning
Molecular representation learning (MRL) is a key step to build the conne...
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05/27/2022
Deep Ensembles for Graphs with Higher-order Dependencies
Graph neural networks (GNNs) continue to achieve state-of-the-art perfor...
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05/24/2022
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks
Learning effective recipe representations is essential in food studies. ...
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05/24/2022
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation
Recipe recommendation systems play an essential role in helping people d...
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03/19/2022
SD2: Slicing and Dicing Scholarly Data for Interactive Evaluation of Academic Performance
Comprehensively evaluating and comparing researchers' academic performan...
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01/12/2022
Predicting Terrorist Attacks in the United States using Localized News Data
Terrorism is a major problem worldwide, causing thousands of fatalities ...
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06/04/2021
Graph Barlow Twins: A self-supervised representation learning framework for graphs
The self-supervised learning (SSL) paradigm is an essential exploration ...
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05/05/2021
DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data
Despite over two decades of progress, imbalanced data is still considere...
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02/16/2021
Few-Shot Graph Learning for Molecular Property Prediction
The recent success of graph neural networks has significantly boosted mo...
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12/29/2020
AttrE2vec: Unsupervised Attributed Edge Representation Learning
Representation learning has overcome the often arduous and manual featur...
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07/25/2020
Learning Attribute-Structure Co-Evolutions in Dynamic Graphs
Most graph neural network models learn embeddings of nodes in static att...
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06/17/2020
Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network
Noun phrases and relational phrases in Open Knowledge Bases are often no...
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06/11/2020
Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors
User behavior modeling is important for industrial applications such as ...
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06/10/2020
Pandemic Pulse: Unraveling and Modeling Social Signals during the COVID-19 Pandemic
We present and begin to explore a collection of social data that represe...
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06/10/2020
Jointly Predicting Job Performance, Personality, Cognitive Ability, Affect, and Well-Being
Assessment of job performance, personalized health and psychometric meas...
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11/26/2019
Few-Shot Knowledge Graph Completion
Knowledge graphs (KGs) serve as useful resources for various natural lan...
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10/07/2019
Graph Few-shot Learning via Knowledge Transfer
Towards the challenging problem of semi-supervised node classification, ...
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08/15/2019
HONEM: Network Embedding Using Higher-Order Patterns in Sequential Data
Representation learning offers a powerful alternative to the oft painsta...
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06/26/2019
Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements
Conditions are essential in the statements of biological literature. Wit...
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04/06/2019
Incremental embedding for temporal networks
Prediction over edges and nodes in graphs requires appropriate and effic...
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11/20/2018
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
Nowadays, multivariate time series data are increasingly collected in va...
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04/11/2018
Long-term Compliance Habits: What Early Data Tells Us
The rise in popularity of physical activity trackers provides extensive ...
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06/01/2017
Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline
From medical charts to national census, healthcare has traditionally ope...
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02/02/2017
HoNVis: Visualizing and Exploring Higher-Order Networks
Unlike the conventional first-order network (FoN), the higher-order netw...
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06/19/2016
Can Scientific Impact Be Predicted?
A widely used measure of scientific impact is citations. However, due to...
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12/15/2014
Will This Paper Increase Your h-index? Scientific Impact Prediction
Scientific impact plays a central role in the evaluation of the output o...
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02/09/2011