70 citations · 111 across the 8 of their papers we have counts for
5 papers · 1 filter
VPNets: Volume-preserving neural networks for learning source-free dynamics
Aiqing Zhu, Beibei Zhu, Jiawei Zhang +2
We propose volume-preserving networks (VPNets) for learning unknown source-free dynamical systems using trajectory data. We propose three modules and combine them to obtain two net…
Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
Zhuohang Li, Luyang Liu, Jiaxin Zhang +1
Federated Learning (FL) enables multiple distributed clients (e.g., mobile devices) to collaboratively train a centralized model while keeping the training data locally on the clie…
Free-riders in Federated Learning: Attacks and Defenses
Jierui Lin, Min Du, Jian Liu
Federated learning is a recently proposed paradigm that enables multiple clients to collaboratively train a joint model. It allows clients to train models locally, and leverages th…
Latent Dirichlet Allocation in Generative Adversarial Networks
Lili Pan, Shen Cheng, Jian Liu +2
We study the problem of multimodal generative modelling of images based on generative adversarial networks (GANs). Despite the success of existing methods, they often ignore the un…
Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction
Yunzhe Tao, Lin Ma, Weizhong Zhang +3
Time series prediction has been studied in a variety of domains. However, it is still challenging to predict future series given historical observations and past exogenous data. Ex…