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Ethan Shi
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Year
From continuous dynamics to graph neural networks: Neural diffusion and beyond
A Han, D Shi, L Lin, J Gao
arXiv preprint arXiv:2310.10121, 2023
202023
Quasi-framelets: Another improvement to graphneural networks
M Yang, X Zheng, J Yin, J Gao
arXiv preprint arXiv:2201.04728, 2022
142022
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond
Z Shao, D Shi, A Han, Y Guo, Q Zhao, J Gao
arXiv preprint arXiv:2309.02769, 2023
122023
How curvature enhance the adaptation power of framelet gcns
D Shi, Y Guo, Z Shao, J Gao
arXiv preprint arXiv:2307.09768, 2023
122023
Generalized energy and gradient flow via graph framelets
A Han, D Shi, Z Shao, J Gao
arXiv preprint arXiv:2210.04124, 2022
122022
Coupling matrix manifolds assisted optimization for optimal transport problems
D Shi, J Gao, X Hong, ST Boris Choy, Z Wang
Machine Learning 110, 533-558, 2021
102021
Enhancing framelet GCNs with generalized p-Laplacian regularization
Z Shao, D Shi, A Han, A Vasnev, Y Guo, J Gao
International Journal of Machine Learning and Cybernetics 15 (4), 1553-1573, 2024
9*2024
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges
D Shi, A Han, L Lin, Y Guo, J Gao
arXiv preprint arXiv:2311.07073, 2023
82023
Design your own universe: A physics-informed agnostic method for enhancing graph neural networks
D Shi, A Han, L Lin, Y Guo, Z Wang, J Gao
International Journal of Machine Learning and Cybernetics, 1-16, 2024
72024
Specstg: A fast spectral diffusion framework for probabilistic spatio-temporal traffic forecasting
L Lin, D Shi, A Han, J Gao
arXiv preprint arXiv:2401.08119, 2024
72024
Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion
D Shi, Z Shao, Y Guo, Q Zhao, J Gao
Transactions on Machine Learning Research, 0
5*
Bregman Graph Neural Network
J Zhai, L Lin, D Shi, J Gao
arXiv preprint arXiv:2309.06645, 2023
42023
Frameless graph knowledge distillation
D Shi, Z Shao, J Gao, Z Wang, Y Guo
IEEE Transactions on Neural Networks and Learning Systems, 2024
32024
Quasi-framelets: robust graph neural networks via adaptive framelet convolution
M Yang, D Shi, X Zheng, J Yin, J Gao
International Journal of Machine Learning and Cybernetics, 1-16, 2024
22024
Fixed Point Laplacian Mapping: A Geometrically Correct Manifold Learning Algorithm
D Shi, A Han, Y Guo, J Gao
2023 International Joint Conference on Neural Networks (IJCNN), 1-9, 2023
22023
Unleash Graph Neural Networks from Heavy Tuning
L Lin, D Shi, A Han, Z Wang, J Gao
arXiv preprint arXiv:2405.12521, 2024
12024
A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models
D Shi, Z Shao, A Han, Y Guo, G Junbin
Asian Conference on Machine Learning, 1199-1214, 2024
12024
Generalized Laplacian Regularized Framelet Graph Neural Networks
Z Shao, A Han, D Shi, A Vasnev, J Gao
arXiv preprint arXiv:2210.15092, 2022
12022
A discussion on the validity of manifold learning
D Shi, A Han, Y Guo, J Gao
arXiv preprint arXiv:2106.01608, 2021
12021
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
L Lin, D Shi, A Han, Z Wang, J Gao
arXiv preprint arXiv:2410.05697, 2024
2024
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