7 citations · 17 across the 5 of their papers we have counts for
5 papers
EDEN: A Plug-in Equivariant Distance Encoding to Beyond the 1-WL Test
Chang Liu, Yuwen Yang, Yue Ding +1
The message-passing scheme is the core of graph representation learning. While most existing message-passing graph neural networks (MPNNs) are permutation-invariant in graph-level…
Completely Heterogeneous Federated Learning
Chang Liu, Yuwen Yang, Xun Cai +2
Federated learning (FL) faces three major difficulties: cross-domain, heterogeneous models, and non-i.i.d. labels scenarios. Existing FL methods fail to handle the above three cons…
NoMorelization: Building Normalizer-Free Models from a Sample's Perspective
Chang Liu, Yuwen Yang, Yue Ding +1
The normalizing layer has become one of the basic configurations of deep learning models, but it still suffers from computational inefficiency, interpretability difficulties, and l…
LRNNet: A Light-Weighted Network with Efficient Reduced Non-Local Operation for Real-Time Semantic Segmentation
Weihao Jiang, Zhaozhi Xie, Yaoyi Li +2
The recent development of light-weighted neural networks has promoted the applications of deep learning under resource constraints and mobile applications. Many of these applicatio…
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers
Xishan Zhang, Shaoli Liu, Rui Zhang +8
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers. Recent emerged quantization technique has been applied to inference of deep neur…