research
∙
08/10/2023
Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification
Patent classification aims to assign multiple International Patent Class...
share
research
∙
05/21/2023
Learning Joint 2D 3D Diffusion Models for Complete Molecule Generation
Designing new molecules is essential for drug discovery and material sci...
research
∙
03/23/2023
Towards Better Dynamic Graph Learning: New Architecture and Unified Library
We propose DyGFormer, a new Transformer-based architecture for dynamic g...
research
∙
02/20/2023
PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation
Spatiotemporal data mining plays an important role in air quality monito...
research
∙
01/01/2023
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
Learning the underlying distribution of molecular graphs and generating ...
research
∙
12/04/2022
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation
Graph generative models have broad applications in biology, chemistry an...
research
∙
12/01/2022
Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning
The essential task of urban planning is to generate the optimal land-use...
research
∙
09/26/2022
Automated Urban Planning aware Spatial Hierarchies and Human Instructions
Traditional urban planning demands urban experts to spend considerable t...
research
∙
06/30/2022
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction
Traffic demand forecasting by deep neural networks has attracted widespr...
research
∙
06/28/2022
Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting
Recent studies have shown great promise in applying graph neural network...
research
∙
05/31/2022
Label-Enhanced Graph Neural Network for Semi-supervised Node Classification
Graph Neural Networks (GNNs) have been widely applied in the semi-superv...
research
∙
05/29/2022
Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction
Recent years have witnessed a rapid growth of applying deep spatiotempor...
research
∙
05/05/2022
Exploiting Global and Local Hierarchies for Hierarchical Text Classification
Hierarchical text classification aims to leverage label hierarchy in mul...
research
∙
04/12/2022
Modelling Evolutionary and Stationary User Preferences for Temporal Sets Prediction
Given a sequence of sets, where each set is associated with a timestamp ...
research
∙
10/12/2021
Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning
Urban planning designs land-use configurations and can benefit building ...
research
∙
09/27/2021
Analysis for full face mechanical behaviors through spatial deduction model with real-time monitoring data
Mechanical analysis for the full face of tunnel structure is crucial to ...
research
∙
05/24/2021
Heterogeneous Graph Representation Learning with Relation Awareness
Representation learning on heterogeneous graphs aims to obtain meaningfu...
research
∙
01/09/2021
LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification
Extreme Multi-label text Classification (XMC) is a task of finding the m...
research
∙
12/29/2020
Hybrid Micro/Macro Level Convolution for Heterogeneous Graph Learning
Heterogeneous graphs are pervasive in practical scenarios, where each gr...
research
∙
12/15/2020
Coupled Layer-wise Graph Convolution for Transportation Demand Prediction
Graph Convolutional Network (GCN) has been widely applied in transportat...
research
∙
08/26/2020
Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection
While Water Treatment Networks (WTNs) are critical infrastructures for l...
research
∙
06/20/2020
