research
∙
09/20/2022
A Simple Temporal Information Matching Mechanism for Entity Alignment Between Temporal Knowledge Graphs
Entity alignment (EA) aims to find entities in different knowledge graph...
share
research
∙
05/25/2022
Restricted mean survival time regression model with time-dependent covariates
In clinical or epidemiological follow-up studies, methods based on time ...
research
∙
10/14/2021
A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation
Pun location is to identify the punning word (usually a word or a phrase...
research
∙
08/13/2021
BESS Aided Reconfigurable Energy Supply using Deep Reinforcement Learning for 5G and Beyond
The year of 2020 has witnessed the unprecedented development of 5G netwo...
research
∙
06/25/2021
Implementation of an alternative method for assessing competing risks: restricted mean time lost
In clinical and epidemiological studies, hazard ratios are often applied...
research
∙
06/20/2021
Dynamic prediction and analysis based on restricted mean survival time in survival analysis with nonproportional hazards
In the process of clinical diagnosis and treatment, the restricted mean ...
research
∙
02/09/2021
On Explainability of Graph Neural Networks via Subgraph Explorations
We consider the problem of explaining the predictions of graph neural ne...
research
∙
01/22/2021
Mixed Finite Element Discretization for Maxwell Viscoelastic Model of Wave Propagation
This paper considers semi-discrete and fully discrete mixed finite eleme...
research
∙
01/06/2021
Node2Seq: Towards Trainable Convolutions in Graph Neural Networks
Investigating graph feature learning becomes essentially important with ...
research
∙
12/31/2020
Explainability in Graph Neural Networks: A Taxonomic Survey
Deep learning methods are achieving ever-increasing performance on many ...
research
∙
11/17/2020
Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping
Grouping has been commonly used in deep metric learning for computing di...
research
∙
10/21/2020
Self-Supervised Contrastive Learning for Efficient User Satisfaction Prediction in Conversational Agents
Turn-level user satisfaction is one of the most important performance me...
research
∙
07/18/2020
Deep Learning of High-Order Interactions for Protein Interface Prediction
Protein interactions are important in a broad range of biological proces...
research
∙
06/03/2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks
Graphs neural networks (GNNs) learn node features by aggregating and com...
research
∙
05/29/2020
Large-scale Hybrid Approach for Predicting User Satisfaction with Conversational Agents
Measuring user satisfaction level is a challenging task, and a critical ...
research
∙
07/08/2019
XFake: Explainable Fake News Detector with Visualizations
In this demo paper, we present the XFake system, an explainable fake new...
research
∙
07/01/2019
Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images
Visualizing the details of different cellular structures is of great imp...
research
∙
05/18/2017
Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions
The key idea of variational auto-encoders (VAEs) resembles that of tradi...
research
∙
05/18/2017
