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Are High-Degree Representations Really Unnecessary in Equivariant Graph
  Neural Networks?

Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?

15 October 2024
Jiacheng Cen
Anyi Li
Ning Lin
Yuxiang Ren
Zihe Wang
Wenbing Huang
ArXivPDFHTML

Papers citing "Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?"

3 / 3 papers shown
Title
Geometric Trajectory Diffusion Models
Geometric Trajectory Diffusion Models
Jiaqi Han
Minkai Xu
Aaron Lou
Haotian Ye
Stefano Ermon
DiffM
35
4
0
16 Oct 2024
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction
Junjie Xu
Artem Moskalev
Tommaso Mansi
Mangal Prakash
Rui Liao
AI4CE
26
1
0
15 Oct 2024
On the Completeness of Invariant Geometric Deep Learning Models
On the Completeness of Invariant Geometric Deep Learning Models
Zian Li
Xiyuan Wang
Shijia Kang
Muhan Zhang
20
2
0
07 Feb 2024
1