ARFA: An Asymmetric Receptive Field Autoencoder Model for Spatiotemporal Prediction

no code implementations • 1 Sep 2023 • Wenxuan Zhang, Xuechao Zou, Li Wu, Xiaoying Wang, Jianqiang Huang, Junliang Xing

Additionally, we construct the RainBench, a large-scale radar echo dataset for precipitation prediction, to address the scarcity of meteorological data in the domain.

Weather Forecasting

Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength

no code implementations • 3 Oct 2022 • Chen Zhao, Joyce H Keyak, Xuewei Cao, Qiuying Sha, Li Wu, Zhe Luo, LanJuan Zhao, Qing Tian, Chuan Qiu, Ray Su, Hui Shen, Hong-Wen Deng, Weihua Zhou

The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion.

Representation Learning Variational Inference

Failure Identification from Unstable Log Data using Deep Learning

1 code implementation • 6 Apr 2022 • Jasmin Bogatinovski, Sasho Nedelkoski, Li Wu, Jorge Cardoso, Odej Kao

Our experimental results demonstrate that the learned subprocesses representations reduce the instability in the input, allowing CLog to outperform the baselines on the failure identification subproblems - 1) failure detection by 9-24% on F1 score and 2) failure type identification by 7% on the macro averaged F1 score.