检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

907 篇 期刊文献
618 篇 会议
12 篇 学位论文

馆藏范围

1,537 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,386 篇 工学
- 946 篇 计算机科学与技术...
- 488 篇 电气工程
- 177 篇 信息与通信工程
- 129 篇 控制科学与工程
- 128 篇 软件工程
- 75 篇 生物医学工程（可授...
- 73 篇 仪器科学与技术
- 59 篇 机械工程
- 48 篇 材料科学与工程（可...
- 36 篇 电子科学与技术（可...
- 32 篇 石油与天然气工程
- 25 篇 测绘科学与技术
- 24 篇 化学工程与技术
- 21 篇 土木工程
- 21 篇 环境科学与工程（可...
- 19 篇 动力工程及工程热...
- 17 篇 力学（可授工学、理...
- 16 篇 交通运输工程
- 13 篇 生物工程
327 篇 理学
- 124 篇 物理学
- 95 篇 生物学
- 59 篇 化学
- 54 篇 数学
- 35 篇 地球物理学
- 20 篇 统计学（可授理学、...
243 篇 医学
- 146 篇 临床医学
- 61 篇 特种医学
- 56 篇 基础医学(可授医学...
109 篇 管理学
- 88 篇 管理科学与工程(可...
- 15 篇 图书情报与档案管...
18 篇 农学
12 篇 经济学
10 篇 法学
10 篇 教育学
9 篇 文学
3 篇 艺术学

主题

1,537 篇 variational auto...
260 篇 deep learning
131 篇 anomaly detectio...
93 篇 machine learning
59 篇 generative adver...
47 篇 generative model
46 篇 training
43 篇 feature extracti...
42 篇 unsupervised lea...
39 篇 neural networks
37 篇 representation l...
36 篇 generative adver...
36 篇 data augmentatio...
34 篇 convolutional ne...
33 篇 data models
27 篇 semi-supervised ...
27 篇 artificial intel...
26 篇 task analysis
26 篇 deep generative ...
25 篇 collaborative fi...

机构

10 篇 natl chiao tung ...
6 篇 ucl england
6 篇 shenzhen univ co...
6 篇 shanghai univ sc...
5 篇 nanyang technol ...
5 篇 zhejiang lab peo...
5 篇 xiamen univ sch ...
5 篇 chung yuan chris...
4 篇 mit comp sci & a...
4 篇 univ chinese aca...
4 篇 beijing jiaotong...
4 篇 acad sinica res ...
4 篇 acad sinica taiw...
4 篇 oak ridge natl l...
4 篇 northwestern pol...
4 篇 ecole technol su...
4 篇 chongqing univ p...
4 篇 tsinghua univ de...
4 篇 univ elect sci &...
4 篇 zhejiang univ st...

作者

12 篇 chien jen-tzung
8 篇 tahan antoine
8 篇 chen junghui
8 篇 zemouri ryad
7 篇 yang fan
7 篇 utschick wolfgan...
7 篇 zhang hao
6 篇 tsao yu
6 篇 baur michael
6 篇 slavic giulia
6 篇 wang hsin-min
6 篇 regazzoni carlo
6 篇 marcenaro lucio
5 篇 guo rui
5 篇 li maokun
5 篇 hsu wei-ning
5 篇 glass james
5 篇 liu xin
5 篇 yoshii kazuyoshi
5 篇 li yan

语言

1,489 篇 英文
38 篇 其他
2 篇 中文
1 篇 德文
1 篇 法文
1 篇 意大利文
1 篇 朝鲜文
1 篇 土耳其文

检索条件"主题词=Variational autoencoder"

共 1537 条记录，以下是1241-1250 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Cross-utterance Conditioned Coherent Speech Editing 24

Cross-utterance Conditioned Coherent Speech Editing

引用

Interspeech Conference

作者： Yu, Cheng Li, Yang Zu, Weiqin Sun, Fanglei Tian, Zheng Wang, Jun ShanghaiTech Univ Shanghai Peoples R China Univ Manchester Manchester Lancs England UCL London England

Text-based speech editing systems are developed to enable users to modify speech based on the transcript. Existing state-of-the-art editing systems based on neural networks do partial inferences with no exception, that is, only generate new words that need to be replaced or inserted. This manner usually leads to the prosody of the edited part being inconsistent with the surrounding speech and a failure to handle the alteration of intonation. To address these problems, we propose a cross-utterance conditioned coherent speech editing system, that first does the entire reasoning at the inference time. Our proposed system can generate speech by utilizing speaker information, context, acoustic features, and the mel-spectrogram from the original audio. Experiments conducted on subjective and objective metrics demonstrate that our approach outperforms the baseline on various editing operations regarding naturalness and prosody consistency.

关键词： speech editing variational autoencoder

来源：评论

学校读者我要写书评

暂无评论

Personalization Disentanglement for Federated Learning

Personalization Disentanglement for Federated Learning

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Yan, Peng Long, Guodong Univ Technol Sydney Fac Engn & IT Sydney NSW Australia

ISBN: (纸本)9781665468916

Personalized federated learning (PFL) jointly trains a variety of local models through balancing between knowledge sharing across clients and model personalization per client. This paper addresses PFL via explicit disentangling latent representations into two parts to capture the shared knowledge and client-specific personalization, which leads to more reliable and effective PFL. The disentanglement is achieved by a novel Federated Dual variational autoencoder (FedDVA), which employs two encoders to infer the two types of representations. FedDVA can produce a better understanding of the trade-off between global knowledge sharing and local personalization in PFL. Moreover, it can be integrated with existing FL methods and turn them into personalized models for heterogeneous downstream tasks. Extensive experiments validate the advantages caused by disentanglement and show that models trained with disentangled representations substantially outperform those vanilla methods.

关键词： Federated Learning Disentanglement variational autoencoder

来源：评论

学校读者我要写书评

暂无评论

Disentangled Representation with Causal Constraints for Counterfactual Fairness 27th

Disentangled Representation with Causal Constraints for Coun...

引用

27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

作者： Xu, Ziqi Liu, Jixue Cheng, Debo Li, Jiuyong Liu, Lin Wang, Ke Univ South Australia Adelaide SA Australia Simon Fraser Univ Burnaby BC Canada

ISBN: (纸本)9783031333736;9783031333743

Much research has been devoted to the problem of learning fair representations;however, they do not explicitly state the relationship between latent representations. In many real-world applications, there may be causal relationships between latent representations. Furthermore, most fair representation learning methods focus on group-level fairness and are based on correlation, ignoring the causal relationships underlying the data. In this work, we theoretically demonstrate that using the structured representations enables downstream predictive models to achieve counterfactual fairness, and then we propose the Counterfactual Fairness variational autoencoder (CF-VAE) to obtain structured representations with respect to domain knowledge. The experimental results show that the proposed method achieves better fairness and accuracy performance than the benchmark fairness methods.

关键词： Counterfactual Fairness Representation Learning variational autoencoder

来源：评论

学校读者我要写书评

暂无评论

Automatic Phenotyping by a Seed-guided Topic Model 22

Automatic Phenotyping by a Seed-guided Topic Model

引用

28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KKD)

作者： Song, Ziyang Hu, Yuanyi Verma, Aman Buckeridge, David L. Li, Yue McGill Univ Sch Comp Sci Montreal PQ Canada McGill Univ Dept Math & Stat Montreal PQ Canada McGill Univ Sch Populat & Global Hlth Montreal PQ Canada

ISBN: (纸本)9781450393850

Electronic health records (EHRs) provide rich clinical information and the opportunities to extract epidemiological patterns to understand and predict patient disease risks with suitable machine learning methods such as topic models. However, existing topic models do not generate identifiable topics each predicting a unique phenotype. One promising direction is to use known phenotype concepts to guide topic inference. We present a seed-guided Bayesian topic model called MixEHR-Seed with 3 contributions: (1) for each phenotype, we infer a dual-form of topic distribution: a seed-topic distribution over a small set of key EHR codes and a regular topic distribution over the entire EHR vocabulary;(2) we model age-dependent disease progression as Markovian dynamic topic priors;(3) we infer seed-guided multi-modal topics over distinct EHR data types. For inference, we developed a variational inference algorithm. Using MixEHR-Seed, we inferred 1569 PheCode-guided phenotype topics from an EHR database in Quebec, Canada covering 1.3 million patients for up to 20-year follow-up with 122 million records for 8539 and 1126 unique diagnostic and drug codes, respectively. We observed (1) accurate phenotype prediction by the guided topics, (2) clinically relevant PheCode-guided disease topics, (3) meaningful age-dependent disease prevalence. Source code is available at GitHub.

关键词： topic modeling variational autoencoder electronic health records predictive healthcare

来源：评论

学校读者我要写书评

暂无评论

Prediction of MGMT Methylation Status of Glioblastoma Using Radiomics and Latent Space Shape Features 7th

Prediction of MGMT Methylation Status of Glioblastoma Using ...

引用

7th International Brain Lesion Workshop (BrainLes)

作者： Palsson, Sveinn Cerri, Stefano Van Leemput, Koen Tech Univ Denmark Dept Hlth Technol Lyngby Denmark Harvard Med Sch Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Boston MA 02115 USA

ISBN: (纸本)9783031090028;9783031090011

In this paper we propose a method for predicting the status of MGMT promoter methylation in high-grade gliomas. From the available MR images, we segment the tumor using deep convolutional neural networks and extract both radiomic features and shape features learned by a variational autoencoder. We implemented a standard machine learning workflow to obtain predictions, consisting of feature selection followed by training of a random forest classification model. We trained and evaluated our method on the RSNA-ASNR-MICCAI BraTS 2021 challenge dataset and submitted our predictions to the challenge.

关键词： MGMT prediction Radiomics Deep learning Glioblastoma variational autoencoder

来源：评论

学校读者我要写书评

暂无评论

GENERALIZED ZERO-SHOT LEARNING USING CONDITIONAL WASSERSTEIN autoencoder 47

GENERALIZED ZERO-SHOT LEARNING USING CONDITIONAL WASSERSTEIN...

引用

47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Kim, Junhan Shim, Byonghyo Seoul Natl Univ Dept Elect & Comp Engn Seoul South Korea

ISBN: (纸本)9781665405409

Generalized zero-shot learning (GZSL) is a technique to train a deep learning model to identify unseen classes. Conventionally, conditional generative models have been employed to generate training data for unseen classes from the attribute. In this paper, we propose a new conditional generative model that improves the GZSL performance greatly. In a nutshell, the proposed model, called conditional Wasserstein autoencoder (CWAE), minimizes the Wasserstein distance between the real and generated image feature distributions using an encoder-decoder architecture. From the extensive experiments on various benchmark datasets, we show that the proposed CWAE outperforms conventional generative models in terms of the GZSL classification performance.

关键词： Generalized zero-shot learning generative model generative adversarial network variational autoencoder

来源：评论

学校读者我要写书评

暂无评论

Interpretable Style Transfer for Text-to-Speech with ControlVAE and Diffusion Bridge 24

Interpretable Style Transfer for Text-to-Speech with Control...

引用

Interspeech Conference

作者： Guan, Wenhao Li, Tao Li, Yishuang Huang, Hukai Hong, Qingyang Li, Lin Xiamen Univ Sch Informat Xiamen Peoples R China Xiamen Univ Inst Artificial Intelligence Xiamen Peoples R China Xiamen Univ Sch Elect Sci & Engn Xiamen Peoples R China

With the demand for autonomous control and personalized speech generation, the style control and transfer in Text-to-Speech (TTS) is becoming more and more important. In this paper, we propose a new TTS system that can perform style transfer with interpretability and high fidelity. Firstly, we design a TTS system that combines variational autoencoder (VAE) and diffusion refiner to get refined mel-spectrograms. Specifically, a two-stage and a one-stage system are designed respectively, to improve the audio quality and the performance of style transfer. Secondly, a diffusion bridge of quantized VAE is designed to efficiently learn complex discrete style representations and improve the performance of style transfer. To have a better ability of style transfer, we introduce ControlVAE to improve the reconstruction quality and have good interpretability simultaneously. Experiments on LibriTTS dataset demonstrate that our method is more effective than baseline models

关键词： speech synthesis style transfer variational autoencoder diffusion probabilistic model

来源：评论

学校读者我要写书评

暂无评论

Improving Neural Topic Models with Wasserstein Knowledge Distillation 1

引用

45th European Conference on Information Retrieval (ECIR)

作者： Adhya, Suman Sanyal, Debarshi Kumar Indian Assoc Cultivat Sci Jadavpur 700032 India

ISBN: (数字)9783031282386

ISBN: (纸本)9783031282379;9783031282386

Topic modeling is a dominant method for exploring document collections on the web and in digital libraries. Recent approaches to topic modeling use pretrained contextualized language models and variational autoencoders. However, large neural topic models have a considerable memory footprint. In this paper, we propose a knowledge distillation framework to compress a contextualized topicmodel without loss in topic quality. In particular, the proposed distillation objective is to minimize the cross-entropy of the soft labels produced by the teacher and the student models, as well as to minimize the squared 2-Wasserstein distance between the latent distributions learned by the two models. Experiments on two publicly available datasets show that the student trained with knowledge distillation achieves topic coherence much higher than that of the original student model, and even surpasses the teacher while containing far fewer parameters than the teacher. The distilled model also outperforms several other competitive topic models on topic coherence.

关键词： Topic modeling Knowledge distillation Wasserstein distance Contextualized topic model variational autoencoder

来源：评论

学校读者我要写书评

暂无评论

Automatic Fault Detection for Marine Diesel Engine Degradation in Autonomous Ferry Crossing Operation 16

Automatic Fault Detection for Marine Diesel Engine Degradati...

引用

16th IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Ellefsen, Andre Listou Cheng, Xu Holmeset, Finn Tore Aesoy, Vilmar Zhang, Houxiang Ushakov, Sergey Norwegian Univ Sci & Technol Dept Ocean Operat & Civil Engn Mechatron Lab N-6009 Alesund Norway Norwegian Univ Sci & Technol Dept Marine Technol N-7491 Trondheim Norway

ISBN: (纸本)9781728116976

The maritime industry generally anticipates having semi-autonomous ferries in commercial use on the west coast of Norway by the end of this decade. In order to schedule maintenance operations of critical components in a secure and cost-effective manner, a reliable prognostics and health management system is essential during autonomous operations. Any remaining useful life prediction obtained from such system should depend on an automatic fault detection algorithm. In this study, an unsupervised reconstruction-based fault detection algorithm is used to predict faults automatically in a simulated autonomous ferry crossing operation. The benefits of the algorithm are confirmed on data sets of real-operational data from a marine diesel engine collected from a hybrid power lab. During the ferry crossing operation, the engine is subjected to drastic changes in operational loads. This increases the difficulty of the algorithm to detect faults with high accuracy. Thus, to support the algorithm, three different feature selection processes on the input data is compared. The results suggest that the algorithm achieves the highest prediction accuracy when the input data is subjected to feature selection based on sensitivity analysis.

关键词： Automatic fault detection feature selection marine diesel engine prognostics and health management variational autoencoder

来源：评论

学校读者我要写书评

暂无评论

Smart Meter Data Anomaly Detection Using variational Recurrent autoencoders with Attention 4th

Smart Meter Data Anomaly Detection Using Variational Recurre...

引用

4th International Conference on Intelligent Technologies and Applications (INTAP)

作者： Dai, Wenjing Liu, Xiufeng Heller, Alfred Nielsen, Per Sieverts Tech Univ Denmark Dept Technol Management & Econ DK-2800 Lyngby Denmark Niras OStre Havnegade 12 DK-9000 Aalborg Denmark

ISBN: (纸本)9783031105258;9783031105241

In the digitization of energy systems, sensors and smart meters are increasingly being used to monitor production, operation and demand. Detection of anomalies based on smart meter data is crucial to identify potential risks and unusual events at an early stage, which can serve as a reference for timely initiation of appropriate actions and improving management. However, smart meter data from energy systems often lack labels and contain noise and various patterns without distinctively cyclical. Meanwhile, the vague definition of anomalies in different energy scenarios and highly complex temporal correlations pose a great challenge for anomaly detection. Many traditional unsupervised anomaly detection algorithms such as cluster-based or distance-based models are not robust to noise and not fully exploit the temporal dependency in a time series as well as other dependencies amongst multiple variables (sensors). This paper proposes an unsupervised anomaly detection method based on a variational Recurrent autoencoder with attention mechanism. with "dirty" data from smart meters, our method pre-detects missing values and global anomalies to shrink their contribution while training. This paper makes a quantitative comparison with the VAE-based baseline approach and four other unsupervised learning methods, demonstrating its effectiveness and superiority. This paper further validates the proposed method by a real case study of detecting the anomalies of water supply temperature from an industrial heating plant.

关键词： Anomaly detection variational autoencoder Smart meter data Attention mechanism

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共154页 << < 121 122 123 124 125 126 127 128 129 130 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：