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20222026
most citedResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization

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

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cs.LG2026

Same Target, Different Origins: Aligning Latent Rollout for Consistent PDE Emulation

Xinying Li, Jing Xu, Wenjun Wang +4

Neural PDE solvers commonly generate multi-step predictions through autoregressive rollout, recursively applying a learned evolution operator and feeding each prediction back as in…

cs.LG2024

CENTAUR: Bridging the Impossible Trinity of Privacy, Efficiency, and Performance in Privacy-Preserving Transformer Inference

Jinglong Luo, Guanzhong Chen, Yehong Zhang +6

With the growing deployment of pre-trained models like Transformers on cloud platforms, privacy concerns about model parameters and inference data are intensifying. Existing Privac…

cs.LG2024

Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs

Langzhang Liang, Sunwoo Kim, Kijung Shin +3

Graph Neural Networks (GNNs) have gained significant attention as a powerful modeling and inference method, especially for homophilic graph-structured data. To empower GNNs in hete…

cs.LG2024

PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations

Shiyi Qi, Zenglin Xu, Yiduo Li +4

Recent advancements in deep learning have led to the development of various models for long-term multivariate time-series forecasting (LMTF), many of which have shown promising res…

cs.LG2022★ 5 cited

ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization

Langzhang Liang, Zenglin Xu, Zixing Song +3

Graph Neural Networks (GNNs) have attracted much attention due to their ability in learning representations from graph-structured data. Despite the successful applications of GNNs…