no code implementations • 28 Dec 2023 • Yan Ding, Hao Cheng, Ziliang Ye, Ruyi Feng, Wei Tian, Peng Xie, Juan Zhang, Zhongze Gu
We fine-tuned our proposed pre-trained model on six molecular property prediction tasks (MoleculeNet datasets) and two generative tasks (ZINC250K datasets), achieving state-of-the-art (SOTA) results on five out of eight tasks.
no code implementations • 27 Oct 2023 • Peng Xie, Zihao Xin, Yang Wang, Shengjun Huang, Tsz Wai Chan, Kani Chen
We proposed a novel evaluation metric called FAL, which assesses an Automatic Speech Recognition (ASR) system based on fidelity to the original audio, accuracy, and latency.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 7 Aug 2023 • Kerui Huang, Jianhong Tian, Lei Sun, Li Zeng, Peng Xie, Aihua Deng, Ping Mo, Zhibo Zhou, Ming Jiang, Yun Wang, Xiaocheng Jiang
Gene mining is an important topic in the field of life sciences, but traditional machine learning methods cannot consider the regulatory relationships between genes.
no code implementations • 6 Apr 2022 • Peng Xie, Minbo Ma, Tianrui Li, Shenggong Ji, Shengdong Du, Zeng Yu, Junbo Zhang
Second, we employ a dynamic graph relationship learning module to learn dynamic spatial relationships between metro stations without a predefined graph adjacency matrix.
no code implementations • 22 Jan 2022 • Minbo Ma, Peng Xie, Fei Teng, Tianrui Li, Bin Wang, Shenggong Ji, Junbo Zhang
In this paper, we propose a novel Hierarchical Spatio-Temporal Graph Neural Network (HiSTGNN) to model cross-regional spatio-temporal correlations among meteorological variables in multiple stations.
no code implementations • 24 Apr 2021 • Peng Xie, Wenyuan Tao, Jie Li, Wentao Huang, Siming Chen
The core of the approach is a subset embedding network (SEN) that represents a group of subsets as uniformly-formatted embeddings.
no code implementations • 19 Mar 2020 • Donghuan Lu, Sujun Zhao, Peng Xie, Kai Ma, Li-Juan Liu, Yefeng Zheng
To ensure the quality of reconstructed neurons and provide guidance for annotators to improve their efficiency, we propose a deep learning based quality control method for neuron reconstruction in this paper.
no code implementations • 26 Aug 2019 • Peng Xie, Tianrui Li, Jia Liu, Shengdong Du, Xin Yang, Junbo Zhang
Urban spatial-temporal flows prediction is of great importance to traffic management, land use, public safety, etc.