Hao Yuan | DeepAI

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Featured Co-authors

Fan Yang
225 publications
Wei Wei
156 publications
YI LIU
156 publications
Jie Wang
115 publications
Xia Hu
111 publications
Jiliang Tang
103 publications
Zheng Chen
71 publications
Shuiwang Ji
56 publications
Kang Li
43 publications
Cheng Deng
41 publications
Mengnan Du
40 publications

∙ 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...

0 Li Cai, et al. ∙

∙ 05/25/2022

Restricted mean survival time regression model with time-dependent covariates

In clinical or epidemiological follow-up studies, methods based on time ...

0 Chengfeng Zhang, et al. ∙

∙ 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...

0 Shen Liu, et al. ∙

∙ 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...

0 Hao Yuan, et al. ∙

∙ 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...

0 Hongji Wu, et al. ∙

∙ 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 ...

0 Zijing Yang, et al. ∙

∙ 02/09/2021

On Explainability of Graph Neural Networks via Subgraph Explorations

We consider the problem of explaining the predictions of graph neural ne...

27 Hao Yuan, et al. ∙

∙ 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...

0 Hao Yuan, et al. ∙

∙ 01/06/2021

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

Investigating graph feature learning becomes essentially important with ...

22 Hao Yuan, et al. ∙

∙ 12/31/2020

Explainability in Graph Neural Networks: A Taxonomic Survey

Deep learning methods are achieving ever-increasing performance on many ...

227 Hao Yuan, et al. ∙

∙ 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...

10 Zhengyang Wang, et al. ∙

∙ 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...

0 Mohammad Kachuee, et al. ∙

∙ 07/18/2020

Deep Learning of High-Order Interactions for Protein Interface Prediction

Protein interactions are important in a broad range of biological proces...

26 YI LIU, et al. ∙

∙ 06/03/2020

XGNN: Towards Model-Level Explanations of Graph Neural Networks

Graphs neural networks (GNNs) learn node features by aggregating and com...

39 Hao Yuan, et al. ∙

∙ 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 ...

0 Dookun Park, et al. ∙

∙ 07/08/2019

XFake: Explainable Fake News Detector with Visualizations

In this demo paper, we present the XFake system, an explainable fake new...

0 Fan Yang, et al. ∙

∙ 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...

0 YI LIU, et al. ∙

∙ 05/18/2017

Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions

The key idea of variational auto-encoders (VAEs) resembles that of tradi...

0 Zhengyang Wang, et al. ∙

∙ 05/18/2017

Pixel Deconvolutional Networks

Deconvolutional layers have been widely used in a variety of deep models...

0 Hongyang Gao, et al. ∙

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