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08/17/2023
On Data Imbalance in Molecular Property Prediction with Pre-training
Revealing and analyzing the various properties of materials is an essent...
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08/16/2023
Is Self-Supervised Pretraining Good for Extrapolation in Molecular Property Prediction?
The prediction of material properties plays a crucial role in the develo...
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07/13/2023
Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations
Precisely recommending candidate news articles to users has always been ...
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04/17/2023
Exploring 360-Degree View of Customers for Lookalike Modeling
Lookalike models are based on the assumption that user similarity plays ...
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02/13/2023
NNKGC: Improving Knowledge Graph Completion with Node Neighborhoods
Knowledge graph completion (KGC) aims to discover missing relations of q...
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01/30/2023
Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods?
In this paper we present a novel method, Knowledge Persistence (𝒦𝒫), for...
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12/12/2022
MegaCRN: Meta-Graph Convolutional Recurrent Network for Spatio-Temporal Modeling
Spatio-temporal modeling as a canonical task of multivariate time series...
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11/27/2022
Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
Traffic forecasting as a canonical task of multivariate time series fore...
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11/22/2022
Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactions
Learning on evolving(dynamic) graphs has caught the attention of researc...
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05/23/2022
KQGC: Knowledge Graph Embedding with Smoothing Effects of Graph Convolutions for Recommendation
Leveraging graphs on recommender systems has gained popularity with the ...
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03/27/2022
mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations
The growing amount of data and advances in data science have created a n...
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03/23/2022
Ethereum Fraud Detection with Heterogeneous Graph Neural Networks
While transactions with cryptocurrencies such as Ethereum are becoming m...
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01/23/2022
Investigating Expressiveness of Transformer in Spectral Domain for Graphs
Transformers have been proven to be inadequate for graph representation ...
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09/16/2021
Efficient Scaling of Dynamic Graph Neural Networks
We present distributed algorithms for training dynamic Graph Neural Netw...
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05/21/2021
Finding All Bounded-Length Simple Cycles in a Directed Graph
A new efficient algorithm is presented for finding all simple cycles tha...
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03/26/2021
Heterogeneous Graph Neural Networks for Multi-label Text Classification
Multi-label text classification (MLTC) is an attractive and challenging ...
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01/18/2021
Time-Efficient and High-Quality Graph Partitioning for Graph Dynamic Scaling
The dynamic scaling of distributed computations plays an important role ...
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06/04/2020
The Impact of COVID-19 on Flight Networks
As COVID-19 transmissions spread worldwide, governments have announced a...
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05/26/2020
Benchmarking Graph Data Management and Processing Systems: A Survey
The development of scalable, representative, and widely adopted benchmar...
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12/04/2019
Exploring Multi-Banking Customer-to-Customer Relations in AML Context with Poincaré Embeddings
In the recent years money laundering schemes have grown in complexity an...
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09/24/2019
Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis
Recently, there has been a surge of interest in the use of machine learn...
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09/19/2019
Towards Federated Graph Learning for Collaborative Financial Crimes Detection
Financial crime is a large and growing problem, in some way touching alm...
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08/16/2019
Distributed Edge Partitioning for Trillion-edge Graphs
We propose Distributed Neighbor Expansion (Distributed NE), a parallel a...
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02/26/2019
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Graph representation learning resurges as a trending research subject ow...
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12/21/2018
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs
Graph pattern matching algorithms to handle million-scale dynamic graphs...
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11/30/2018
Scalable Graph Learning for Anti-Money Laundering: A First Look
Organized crime inflicts human suffering on a genocidal scale: the Mexic...
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08/19/2018
An incremental local-first community detection method for dynamic graphs
Community detections for large-scale real world networks have been more ...
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04/17/2018
Scalable attribute-aware network embedding with locality
Adding attributes for nodes to network embedding helps to improve the ab...
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04/17/2018
Scalable attribute-aware network embedding with localily
Adding attributes for nodes to network embedding helps to improve the ab...
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02/08/2018
System G Distributed Graph Database
Motivated by the need to extract knowledge and value from interconnected...
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07/24/2017
Full-Network Embedding in a Multimodal Embedding Pipeline
The current state-of-the-art for image annotation and image retrieval ta...
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07/24/2017
Building Graph Representations of Deep Vector Embeddings
Patterns stored within pre-trained deep neural networks compose large an...
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07/19/2017
Can GAN Learn Topological Features of a Graph?
This paper is first-line research expanding GANs into graph topology ana...
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05/22/2017
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks
Transfer learning for feature extraction can be used to exploit deep rep...
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04/22/2017
Medical Text Classification using Convolutional Neural Networks
We present an approach to automatically classify clinical text at a sent...
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03/03/2017
On the Behavior of Convolutional Nets for Feature Extraction
Deep neural networks are representation learning techniques. During trai...
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05/18/2015
Scalable Parallel Numerical Constraint Solver Using Global Load Balancing
We present a scalable parallel solver for numerical constraint satisfact...
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11/06/2014
