Search Results for author: Fan Xu

Found 25 papers, 5 papers with code

DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy

1 code implementation20 May 2018 Yu Li, Fan Xu, Fa Zhang, Pingyong Xu, Mingshu Zhang, Ming Fan, Lihua Li, Xin Gao, Renmin Han

Our method combines the strength of deep learning and statistical inference, where deep learning captures the underlying distribution of the fluorophores that are consistent with the observed time-series fluorescent images by exploring local features and correlation along time-axis, and statistical inference further refines the ultrastructure extracted by deep learning and endues physical meaning to the final image.

Bayesian Inference Super-Resolution +2

CC-Riddle: A Question Answering Dataset of Chinese Character Riddles

2 code implementations28 Jun 2022 Fan Xu, Yunxiang Zhang, Xiaojun Wan

Solving Chinese character riddles is a challenging task that demands understanding of character glyph, general knowledge, and a grasp of figurative language.

General Knowledge Language Modelling +2

PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction

1 code implementation19 May 2023 Hao Wu, Wei Xiong, Fan Xu, Xiao Luo, Chong Chen, Xian-Sheng Hua, Haixin Wang

In this paper, we investigate the challenge of spatio-temporal video prediction, which involves generating future videos based on historical data streams.

Video Prediction

An entity-driven recursive neural network model for chinese discourse coherence modeling

no code implementations14 Apr 2017 Fan Xu, Shujing Du, Maoxi Li, Mingwen Wang

Chinese discourse coherence modeling remains a challenge taskin Natural Language Processing field. Existing approaches mostlyfocus on the need for feature engineering, whichadoptthe sophisticated features to capture the logic or syntactic or semantic relationships acrosssentences within a text. In this paper, we present an entity-drivenrecursive deep modelfor the Chinese discourse coherence evaluation based on current English discourse coherenceneural network model.

Coherence Evaluation Feature Engineering +4

Sentence-level dialects identification in the greater China region

no code implementations8 Jan 2017 Fan Xu, Mingwen Wang, Maoxi Li

Identifying the different varieties of the same language is more challenging than unrelated languages identification.

Sentence Word Alignment

X-ray Plateaus in Gamma-Ray Burst Afterglows and Their Application in Cosmology

no code implementations10 Dec 2020 Fan Xu, Chen-Han Tang, Jin-Jun Geng, Fa-Yin Wang, Yu-Yang Wang, Abudushataer Kuerban, Yong-Feng Huang

After correcting for the redshift evolution, we show that the de-evolved $L-T-E_{\rm{p}}$ correlation can be used as a standard candle.

High Energy Astrophysical Phenomena

A Unified Cognitive Learning Framework for Adapting to Dynamic Environment and Tasks

no code implementations1 Jun 2021 Qihui Wu, Tianchen Ruan, Fuhui Zhou, Yang Huang, Fan Xu, Shijin Zhao, Ya Liu, Xuyang Huang

Many machine learning frameworks have been proposed and used in wireless communications for realizing diverse goals.

Self-Learning

“细粒度英汉机器翻译错误分析语料库”的构建与思考(Construction of Fine-Grained Error Analysis Corpus of English-Chinese Machine Translation and Its Implications)

no code implementations CCL 2020 Bailian Qiu, Mingwen Wang, Maoxi Li, Cong Chen, Fan Xu

机器翻译错误分析旨在找出机器译文中存在的错误, 包括错误类型、错误分布等, 它在机器翻译研究和应用中起着重要作用。该文将人工译后编辑与错误分析结合起来, 对译后编辑操作进行错误标注, 采用自动标注和人工标注相结合的方法, 构建了一个细粒度英汉机器翻译错误分析语料库, 其中每一个标注样本包括源语言句子、机器译文、人工参考译文、译后编辑译文、词错误率和错误类型标注;标注的错误类型包括增词、漏词、错词、词序错误、未译和命名实体翻译错误等。标注的一致性检验表明了标注的有效性;对标注语料的统计分析结果能有效地指导机器翻译系统的开发和人工译员的后编辑。

Machine Translation

Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach

no code implementations28 Jun 2022 Naifu Zhang, Meixia Tao, Jia Wang, Fan Xu

One of the main focuses in distributed learning is communication efficiency, since model aggregation at each round of training can consist of millions to billions of parameters.

Model Compression Quantization

$L_2$BN: Enhancing Batch Normalization by Equalizing the $L_2$ Norms of Features

no code implementations6 Jul 2022 Zhennan Wang, Kehan Li, Runyi Yu, Yian Zhao, Pengchong Qiao, Chang Liu, Fan Xu, Xiangyang Ji, Guoli Song, Jie Chen

In this paper, we analyze batch normalization from the perspective of discriminability and find the disadvantages ignored by previous studies: the difference in $l_2$ norms of sample features can hinder batch normalization from obtaining more distinguished inter-class features and more compact intra-class features.

Acoustic Scene Classification Image Classification +1

FMGNN: Fused Manifold Graph Neural Network

no code implementations3 Apr 2023 Cheng Deng, Fan Xu, Jiaxing Ding, Luoyi Fu, Weinan Zhang, Xinbing Wang

Graph representation learning has been widely studied and demonstrated effectiveness in various graph tasks.

Graph Representation Learning Link Prediction +1

Cooperative Multi-Cell Massive Access with Temporally Correlated Activity

no code implementations19 Apr 2023 Weifeng Zhu, Meixia Tao, Xiaojun Yuan, Fan Xu, Yunfeng Guan

This paper investigates the problem of activity detection and channel estimation in cooperative multi-cell massive access systems with temporally correlated activity, where all access points (APs) are connected to a central unit via fronthaul links.

Action Detection Activity Detection +1

Exploring Global and Local Information for Anomaly Detection with Normal Samples

no code implementations3 Jun 2023 Fan Xu, Nan Wang, Xibin Zhao

To address such problem, we propose an anomaly detection method GALDetector which is combined of global and local information based on observed normal samples.

Anomaly Detection Fraud Detection +1

TopoSeg: Topology-Aware Nuclear Instance Segmentation

no code implementations ICCV 2023 Hongliang He, Jun Wang, Pengxu Wei, Fan Xu, Xiangyang Ji, Chang Liu, Jie Chen

Experiments on three nuclear instance segmentation datasets justify the superiority of TopoSeg, which achieves state-of-the-art performance.

Instance Segmentation Segmentation +1

Joint Location Sensing and Channel Estimation for IRS-Aided mmWave ISAC Systems

no code implementations14 Nov 2023 Zijian Chen, Ming-Min Zhao, Min Li, Fan Xu, Qingqing Wu, Min-Jian Zhao

Based on the estimation results from the first phase, we formulate a Cram\'{e}r-Rao bound (CRB) minimization problem for optimizing IRS reflection coefficients, and through proper reformulations, a low-complexity manifold-based optimization algorithm is proposed to solve this problem.

Bayesian Inference POS

Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection

no code implementations17 Nov 2023 Fan Xu, Nan Wang, Xuezhi Wen, Meiqi Gao, Chaoqun Guo, Xibin Zhao

Graph anomaly detection plays a crucial role in identifying exceptional instances in graph data that deviate significantly from the majority.

Contrastive Learning Graph Anomaly Detection

Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum

no code implementations11 Dec 2023 Fan Xu, Nan Wang, Hao Wu, Xuezhi Wen, Xibin Zhao, Hai Wan

This detector includes a hybrid filtering module and a local environmental constraint module, the two modules are utilized to solve heterophily and label utilization problem respectively.

Binary Classification Fraud Detection

Spatio-Temporal Fluid Dynamics Modeling via Physical-Awareness and Parameter Diffusion Guidance

no code implementations18 Mar 2024 Hao Wu, Fan Xu, Yifan Duan, Ziwei Niu, Weiyan Wang, Gaofeng Lu, Kun Wang, Yuxuan Liang, Yang Wang

This paper proposes a two-stage framework named ST-PAD for spatio-temporal fluid dynamics modeling in the field of earth sciences, aiming to achieve high-precision simulation and prediction of fluid dynamics through spatio-temporal physics awareness and parameter diffusion guidance.

Quantization

Cannot find the paper you are looking for? You can Submit a new open access paper.