Zobrazeno 1 - 10
of 331
pro vyhledávání: '"Bai Junjie"'
Autor:
ZHANG Junwen, DONG Xukai, CHAI Haitao, YANG Lei, ZHAO Shankun, WANG Qian, LYU Yulei, JIA Lele, BAI Junjie, ZHENG Bo, LI Xiaoming, JING Yanfeng
Publikováno v:
Meitan kexue jishu, Vol 51, Iss 2, Pp 95-105 (2023)
Aimed at the phenomenon of variable overburden spatial structures and complex disaster factors in multi-face mining in a geological anomaly area of a mine, taking the actual geological occurrence conditions and mining technology conditions as the eng
Externí odkaz:
https://doaj.org/article/1ebcce58ae144a31bd8a7924320700f8
Autor:
Li, Muyang, Cai, Tianle, Cao, Jiaxin, Zhang, Qinsheng, Cai, Han, Bai, Junjie, Jia, Yangqing, Liu, Ming-Yu, Li, Kai, Han, Song
Diffusion models have achieved great success in synthesizing high-quality images. However, generating high-resolution images with diffusion models is still challenging due to the enormous computational costs, resulting in a prohibitive latency for in
Externí odkaz:
http://arxiv.org/abs/2402.19481
With the dramatically increased number of parameters in language models, sparsity methods have received ever-increasing research focus to compress and accelerate the models. While most research focuses on how to accurately retain appropriate weights
Externí odkaz:
http://arxiv.org/abs/2205.11005
Autor:
Bai, Junjie1 (AUTHOR), Chi, Yangjian1 (AUTHOR), Shangguan, Tong1 (AUTHOR), Lin, Jun1 (AUTHOR), Ye, Yushi1 (AUTHOR), Huang, Jianfeng2 (AUTHOR), Wen, Yahui3 (AUTHOR), Liu, Rong1 (AUTHOR), Chen, Ru1 (AUTHOR), Cai, Weizhong1 (AUTHOR) caiweizhong1967@163.com, Chen, Jianhui1 (AUTHOR) chenjianhui1983@qq.com
Publikováno v:
Scientific Reports. 4/24/2024, Vol. 14 Issue 1, p1-11. 11p.
Autor:
Zhu, Kai, Zhao, Wenyi, Zheng, Zhen, Guo, Tianyou, Zhao, Pengzhan, Zhu, Feiwen, Bai, Junjie, Yang, Jun, Liu, Xiaoyong, Diao, Lansong, Lin, Wei
Many recent machine learning models show dynamic shape characteristics. However, existing AI compiler optimization systems suffer a lot from problems brought by dynamic shape models, including compilation overhead, memory usage, optimization pipeline
Externí odkaz:
http://arxiv.org/abs/2103.05288
Autor:
Paszke, Adam, Gross, Sam, Massa, Francisco, Lerer, Adam, Bradbury, James, Chanan, Gregory, Killeen, Trevor, Lin, Zeming, Gimelshein, Natalia, Antiga, Luca, Desmaison, Alban, Köpf, Andreas, Yang, Edward, DeVito, Zach, Raison, Martin, Tejani, Alykhan, Chilamkurthy, Sasank, Steiner, Benoit, Fang, Lu, Bai, Junjie, Chintala, Soumith
Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible: it provides an imperative and Pythonic programming style that suppor
Externí odkaz:
http://arxiv.org/abs/1912.01703
Autor:
Guo, Zhihui, Bai, Junjie, Lu, Yi, Wang, Xin, Cao, Kunlin, Song, Qi, Sonka, Milan, Yin, Youbing
A novel centerline extraction framework is reported which combines an end-to-end trainable multi-task fully convolutional network (FCN) with a minimal path extractor. The FCN simultaneously computes centerline distance maps and detects branch endpoin
Externí odkaz:
http://arxiv.org/abs/1903.10481
Autor:
Kong, Bin, Wang, Xin, Bai, Junjie, Lu, Yi, Gao, Feng, Cao, Kunlin, Song, Qi, Zhang, Shaoting, Lyu, Siwei, Yin, Youbing
Modeling the sequential information of image sequences has been a vital step of various vision tasks and convolutional long short-term memory (ConvLSTM) has demonstrated its superb performance in such spatiotemporal problems. Nevertheless, the hierar
Externí odkaz:
http://arxiv.org/abs/1902.10053
Autor:
Wu, Chengxin, Wei, Xing, Men, Xue, Xu, Yulong, Bai, Junjie, Wang, Yu, Zhou, Lei, Yu, Yong-Liang, Xu, Zhang-Run, Chen, Ming-Li, Wang, Jian-Hua
Publikováno v:
In Talanta 1 June 2023 258