Lequan Lin

Orcid: 0009-0006-4677-7327

According to our database1, Lequan Lin authored at least 12 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2022
2023
2024
2025
0
1
2
3
4
5
6
7
8
9
1
7
1
1
1
1

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
Design your own universe: a physics-informed agnostic method for enhancing graph neural networks.
Int. J. Mach. Learn. Cybern., February, 2025

2024
A Simple Yet Effective Framelet-Based Graph Neural Network for Directed Graphs.
IEEE Trans. Artif. Intell., April, 2024

Diffusion models for time-series applications: a survey.
Frontiers Inf. Technol. Electron. Eng., January, 2024

From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond.
Trans. Mach. Learn. Res., 2024

Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning.
CoRR, 2024

When Graph Neural Networks Meet Dynamic Mode Decomposition.
CoRR, 2024

Unleash Graph Neural Networks from Heavy Tuning.
CoRR, 2024

SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting.
CoRR, 2024

Bregman Graph Neural Network.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges.
CoRR, 2023

A Magnetic Framelet-Based Convolutional Neural Network for Directed Graphs.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
A Simple Yet Effective SVD-GCN for Directed Graphs.
CoRR, 2022


  Loading...