858 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Shanghai Artificial Intelligence LaboratoryCN102 papers
- University of Chinese Academy of SciencesCN77 papers
- Chinese Academy of SciencesCN73 papers
- Peking UniversityCN67 papers
- Tsinghua UniversityCN65 papers
- Institute of AutomationCN58 papers
- Shandong Institute of AutomationCN35 papers
- Shanghai Jiao Tong UniversityCN34 papers
- Beihang UniversityCN25 papers
- Fudan UniversityCN25 papers
- Center for Excellence in Brain Science and Intelligence TechnologyCN20 papers
- Chinese University of Hong KongHK19 papers
43 papers · 1 filter
Quantum simulation of partial differential equations via Schrodingerisation: technical details
Shi Jin, Nana Liu, Yue Yu
We study a new method - called Schrodingerisation introduced in [Jin, Liu, Yu, arXiv: 2212.13969] - for solving general linear partial differential equations with quantum simulatio…
SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Mingchen Li, Liqi Kang, Yi Xiong +4
Deep learning has been widely used for protein engineering. However, it is limited by the lack of sufficient experimental data to train an accurate model for predicting the functio…
Quantum simulation of partial differential equations via Schrodingerisation
Shi Jin, Nana Liu, Yue Yu
We present a simple new way - called Schrodingerisation - to simulate general linear partial differential equations via quantum simulation. Using a simple new transform, referred t…
Human Image Generation: A Comprehensive Survey
Zhen Jia, Zhang Zhang, Liang Wang +1
Image and video synthesis has become a blooming topic in computer vision and machine learning communities along with the developments of deep generative models, due to its great ac…
An Unsupervised Machine Learning Approach for Ground-Motion Spectra Clustering and Selection
R. Bailey Bond, Pu Ren, Jerome F. Hajjar +1
Clustering analysis of sequence data continues to address many applications in engineering design, aided with the rapid growth of machine learning in applied science. This paper pr…
Slow Motion Matters: A Slow Motion Enhanced Network for Weakly Supervised Temporal Action Localization
Weiqi Sun, Rui Su, Qian Yu +1
Weakly supervised temporal action localization (WTAL) aims to localize actions in untrimmed videos with only weak supervision information (e.g. video-level labels). Most existing m…
Visual-tactile Fusion for Transparent Object Grasping in Complex Backgrounds
Shoujie Li, Haixin Yu, Wenbo Ding +5
The accurate detection and grasping of transparent objects are challenging but of significance to robots. Here, a visual-tactile fusion framework for transparent object grasping un…
Vertical Federated Learning: Concepts, Advances and Challenges
Yang Liu, Yan Kang, Tianyuan Zou +6
Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with different features about the same set of users jointly train machine learning models w…
AF Adapter: Continual Pretraining for Building Chinese Biomedical Language Model
Yongyu Yan, Kui Xue, Xiaoming Shi +3
Continual pretraining is a popular way of building a domain-specific pretrained language model from a general-domain language model. In spite of its high efficiency, continual pret…
Label-Efficient Object Detection via Region Proposal Network Pre-Training
Nanqing Dong, Linus Ericsson, Yongxin Yang +2
Self-supervised pre-training, based on the pretext task of instance discrimination, has fueled the recent advance in label-efficient object detection. However, existing studies foc…
Demystify Transformers & Convolutions in Modern Image Deep Networks
Xiaowei Hu, Min Shi, Weiyun Wang +9
Vision transformers have gained popularity recently, leading to the development of new vision backbones with improved features and consistent performance gains. However, these adva…
2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-center Study
Lingwei Meng, Di Dong, Xin Chen +5
Objective: Radiomics, an emerging tool for medical image analysis, is potential towards precisely characterizing gastric cancer (GC). Whether using one-slice 2D annotation or whole…
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction
Yuancheng Sun, Yimeng Chen, Weizhi Ma +5
Molecular property prediction is essential for drug discovery. In recent years, deep learning methods have been introduced to this area and achieved state-of-the-art performances.…
Space-variant Shack-Hartmann wavefront sensing based on affine transformation estimation
Fan Feng, Chen Liang, Dongdong Chen +7
The space-variant wavefront reconstruction problem inherently exists in deep tissue imaging. In this paper,we propose a framework of Shack-Hartmann wavefront space-variant sensing…
Transfering Low-Frequency Features for Domain Adaptation
Zhaowen Li, Xu Zhao, Chaoyang Zhao +2
Previous unsupervised domain adaptation methods did not handle the cross-domain problem from the perspective of frequency for computer vision. The images or feature maps of differe…
Modeling Two-Way Selection Preference for Person-Job Fit
Chen Yang, Yupeng Hou, Yang Song +3
Person-job fit is the core technique of online recruitment platforms, which can improve the efficiency of recruitment by accurately matching the job positions with the job seekers.…
AMinerGNN: Heterogeneous Graph Neural Network for Paper Click-through Rate Prediction with Fusion Query
Zepeng Huai, Zhe Wang, Yifan Zhu +1
Paper recommendation with user-generated keyword is to suggest papers that simultaneously meet user's interests and are relevant to the input keyword. This is a recommendation task…
PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation
Guotai Wang, Xiangde Luo, Ran Gu +6
Background and Objective: Open-source deep learning toolkits are one of the driving forces for developing medical image segmentation models. Existing toolkits mainly focus on fully…
Efficient Multimodal Transformer with Dual-Level Feature Restoration for Robust Multimodal Sentiment Analysis
Licai Sun, Zheng Lian, Bin Liu +1
With the proliferation of user-generated online videos, Multimodal Sentiment Analysis (MSA) has attracted increasing attention recently. Despite significant progress, there are sti…
High-Frequency Space Diffusion Models for Accelerated MRI
Chentao Cao, Zhuo-Xu Cui, Yue Wang +5
Diffusion models with continuous stochastic differential equations (SDEs) have shown superior performances in image generation. It can serve as a deep generative prior to solving t…
Deep Learning for Unsupervised Anomaly Localization in Industrial Images: A Survey
Xian Tao, Xinyi Gong, Xin Zhang +2
Currently, deep learning-based visual inspection has been highly successful with the help of supervised learning methods. However, in real industrial scenarios, the scarcity of def…
A Data Driven Method for Multi-step Prediction of Ship Roll Motion in High Sea States
Dan Zhang, Xi Zhou, Zi-Hao Wang +2
Ship roll motion in high sea states has large amplitudes and nonlinear dynamics, and its prediction is significant for operability, safety, and survivability. This paper presents a…
Accelerating Vertical Federated Learning
Dongqi Cai, Tao Fan, Yan Kang +4
Privacy, security and data governance constraints rule out a brute force process in the integration of cross-silo data, which inherits the development of the Internet of Things. Fe…
BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation
Yi Zeng, Dongcheng Zhao, Feifei Zhao +16
Spiking neural networks (SNNs) have attracted extensive attentions in Brain-inspired Artificial Intelligence and computational neuroscience. They can be used to simulate biological…