当前标签：theoretical

Graph Neural Networks with Learnable and Optimal Polynomial Bases

馒头and花卷 2023-12-02 16:21 阅读:79 评论:0 推荐:0

Learning Graph Filters for Spectral GNNs via Newton Interpolation

馒头and花卷 2023-11-26 11:23 阅读:41 评论:0 推荐:0

Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited

馒头and花卷 2023-11-23 13:54 阅读:294 评论:0 推荐:0

How Powerful are Spectral Graph Neural Networks?

馒头and花卷 2023-11-20 20:37 阅读:172 评论:0 推荐:0

Learning to rank: from pairwise approach to listwise approach

馒头and花卷 2023-11-19 21:10 阅读:249 评论:0 推荐:1

How Attentive are Graph Attention Networks?

馒头and花卷 2023-11-19 11:12 阅读:367 评论:0 推荐:0

Decoupling the Depth and Scope of Graph Neural Networks

馒头and花卷 2023-11-17 14:39 阅读:240 评论:0 推荐:0

Temporal Point Processes

馒头and花卷 2023-11-09 14:21 阅读:491 评论:0 推荐:0

Is Homophily a Necessity for Graph Neural Networks?

馒头and花卷 2023-10-31 15:50 阅读:84 评论:0 推荐:0

Metropolis Algorithms for Representative Subgraph Sampling

馒头and花卷 2023-10-19 20:40 阅读:27 评论:0 推荐:0

Weighted Nonlocal Laplacian on Interpolation from Sparse Data

馒头and花卷 2023-10-11 16:14 阅读:34 评论:0 推荐:0

Graph transduction via alternating minimization

馒头and花卷 2023-09-12 15:13 阅读:27 评论:0 推荐:0

Graph Construction and b-Matching for Semi-Supervised Learning

馒头and花卷 2023-09-11 14:52 阅读:33 评论:0 推荐:0

How Expressive are Graph Neural Networks in Recommendation

馒头and花卷 2023-09-08 11:36 阅读:58 评论:0 推荐:0

RoPE

馒头and花卷 2023-07-24 17:38 阅读:353 评论:0 推荐:0

Self-attention with Functional Time Representation Learning

馒头and花卷 2023-06-23 16:06 阅读:121 评论:0 推荐:0

Graph Neural Networks Inspired by Classical Iterative Algorithms

馒头and花卷 2023-06-11 09:29 阅读:53 评论:0 推荐:0

DIFFormer Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

馒头and花卷 2023-06-08 13:39 阅读:102 评论:0 推荐:0

Exploiting Positional Information for Session-based Recommendation

馒头and花卷 2023-06-07 13:30 阅读:46 评论:0 推荐:0

Permutation Invariant Graph Generation via Score-Based Generative Modeling

馒头and花卷 2023-05-26 11:16 阅读:202 评论:0 推荐:0