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Hongyang Chen

6 papers hereh-index 8462 citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5
  • last author1

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL1
  • cs.SI1
same name
  • Hongyang Chen — 11 papers, h 28
  • Hongyang Chen — 7 papers, h 6
  • Hongyang Chen — 7 papers, h 21
  • Hongyang Chen — 5 papers, h 7
  • Hongyang Chen — 5 papers, h 5
  • Hongyang Chen — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212023
most citedGive Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

28 citations · 57 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023★ 1 cited

HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks

Guanghui Zhu, Zhennan Zhu, Hongyang Chen +2

Heterogeneous graph neural networks (GNNs) have been successful in handling heterogeneous graphs. In existing heterogeneous GNNs, meta-path plays an essential role. However, recent…

cs.LG2023★ 25 cited

Graph Neural Processes for Spatio-Temporal Extrapolation

Junfeng Hu, Yuxuan Liang, Zhencheng Fan +3

We study the task of spatio-temporal extrapolation that generates data at target locations from surrounding contexts in a graph. This task is crucial as sensors that collect data a…

cs.LG2022★ 1 cited

Path-aware Siamese Graph Neural Network for Link Prediction

Jingsong Lv, Zhao Li, Hongyang Chen +2

In this paper, we propose a Path-aware Siamese Graph neural network(PSG) for link prediction tasks. First, PSG captures both nodes and edge features for given two nodes, namely the…

cs.LG2021

Thompson Sampling for Unimodal Bandits

Long Yang, Zhao Li, Zehong Hu +4

In this paper, we propose a Thompson Sampling algorithm for \emph{unimodal} bandits, where the expected reward is unimodal over the partially ordered arms. To exploit the unimodal…

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