Search Results for author: Hao Yuan

Found 24 papers, 12 papers with code

An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor Isomorphism

1 code implementation ACL 2022 Xin Mao, Meirong Ma, Hao Yuan, Jianchao Zhu, ZongYu Wang, Rui Xie, Wei Wu, Man Lan

Entity alignment (EA) aims to discover the equivalent entity pairs between KGs, which is a crucial step for integrating multi-source KGs. For a long time, most researchers have regarded EA as a pure graph representation learning task and focused on improving graph encoders while paying little attention to the decoding process. In this paper, we propose an effective and efficient EA Decoding Algorithm via Third-order Tensor Isomorphism (DATTI). Specifically, we derive two sets of isomorphism equations: (1) Adjacency tensor isomorphism equations and (2) Gramian tensor isomorphism equations. By combining these equations, DATTI could effectively utilize the adjacency and inner correlation isomorphisms of KGs to enhance the decoding process of EA. Extensive experiments on public datasets indicate that our decoding algorithm can deliver significant performance improvements even on the most advanced EA methods, while the extra required time is less than 3 seconds.

Entity Alignment Graph Representation Learning

KwaiAgents: Generalized Information-seeking Agent System with Large Language Models

1 code implementation8 Dec 2023 Haojie Pan, Zepeng Zhai, Hao Yuan, Yaojia LV, Ruiji Fu, Ming Liu, Zhongyuan Wang, Bing Qin

Driven by curiosity, humans have continually sought to explore and understand the world around them, leading to the invention of various tools to satiate this inquisitiveness.

NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments

no code implementations22 Nov 2023 Xin Ai, Qiange Wang, Chunyu Cao, Yanfeng Zhang, Chaoyi Chen, Hao Yuan, Yu Gu, Ge Yu

After extensive experiments and analysis, we find that existing task orchestrating methods fail to fully utilize the heterogeneous resources, limited by inefficient CPU processing or GPU resource contention.

Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective

no code implementations22 Nov 2023 Hao Yuan, Yajiong Liu, Yanfeng Zhang, Xin Ai, Qiange Wang, Chaoyi Chen, Yu Gu, Ge Yu

Many Graph Neural Network (GNN) training systems have emerged recently to support efficient GNN training.


A Simple Temporal Information Matching Mechanism for Entity Alignment Between Temporal Knowledge Graphs

1 code implementation COLING 2022 Li Cai, Xin Mao, Meirong Ma, Hao Yuan, Jianchao Zhu, Man Lan

However, we believe that it is not necessary to learn the embeddings of temporal information in KGs since most TKGs have uniform temporal representations.

Entity Alignment Entity Embeddings +1

FlowX: Towards Explainable Graph Neural Networks via Message Flows

2 code implementations26 Jun 2022 Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji

We investigate the explainability of graph neural networks (GNNs) as a step toward elucidating their working mechanisms.


A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation

1 code implementation14 Oct 2021 Shen Liu, Meirong Ma, Hao Yuan, Jianchao Zhu, Yuanbin Wu, Man Lan

Pun location is to identify the punning word (usually a word or a phrase that makes the text ambiguous) in a given short text, and pun interpretation is to find out two different meanings of the punning word.

Word Sense Disambiguation

DIG: A Turnkey Library for Diving into Graph Deep Learning Research

1 code implementation23 Mar 2021 Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, Shuiwang Ji

Although there exist several libraries for deep learning on graphs, they are aiming at implementing basic operations for graph deep learning.

Benchmarking Graph Generation +1

On Explainability of Graph Neural Networks via Subgraph Explorations

1 code implementation9 Feb 2021 Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji

To make the tree search more effective, we propose to use Shapley values as a measure of subgraph importance, which can also capture the interactions among different subgraphs.

Semi-discrete and fully discrete mixed finite element methods for Maxwell viscoelastic model of wave propagation

no code implementations22 Jan 2021 Hao Yuan, Xiaoping Xie

Semi-discrete and fully discrete mixed finite element methods are considered for Maxwell-model-based problems of wave propagation in linear viscoelastic solid.

Numerical Analysis Numerical Analysis

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

no code implementations6 Jan 2021 Hao Yuan, Shuiwang Ji

Several graph neural network approaches are proposed for node feature learning and they generally follow a neighboring information aggregation scheme to learn node features.

Explainability in Graph Neural Networks: A Taxonomic Survey

no code implementations31 Dec 2020 Hao Yuan, Haiyang Yu, Shurui Gui, Shuiwang Ji

To facilitate evaluations, we generate a set of benchmark graph datasets specifically for GNN explainability.

Deep Learning of High-Order Interactions for Protein Interface Prediction

no code implementations18 Jul 2020 Yi Liu, Hao Yuan, Lei Cai, Shuiwang Ji

However, these methods do not incorporate the important sequential information from amino acid chains and the high-order pairwise interactions.

Protein Interface Prediction Vocal Bursts Intensity Prediction

XGNN: Towards Model-Level Explanations of Graph Neural Networks

no code implementations3 Jun 2020 Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji

Furthermore, our experimental results indicate that the generated graphs can provide guidance on how to improve the trained GNNs.

Graph Generation valid

XFake: Explainable Fake News Detector with Visualizations

no code implementations8 Jul 2019 Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia Hu

In this demo paper, we present the XFake system, an explainable fake news detector that assists end-users to identify news credibility.


Global Pixel Transformers for Virtual Staining of Microscopy Images

no code implementations1 Jul 2019 Yi Liu, Hao Yuan, Zhengyang Wang, Shuiwang Ji

It is also shown that our proposed global pixel transformer layer is useful to improve the fluorescence image prediction results.

Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions

1 code implementation18 May 2017 Zhengyang Wang, Hao Yuan, Shuiwang Ji

In this work, we propose spatial VAEs that use feature maps of larger size as latent variables to explicitly capture spatial information.

Pixel Deconvolutional Networks

4 code implementations ICLR 2018 Hongyang Gao, Hao Yuan, Zhengyang Wang, Shuiwang Ji

When used in image generation tasks, our PixelDCL can largely overcome the checkerboard problem suffered by regular deconvolution operations.

Decoder Image Generation +2

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