咨询与建议

限定检索结果

文献类型

  • 478 篇 期刊文献
  • 337 篇 会议
  • 1 册 图书

馆藏范围

  • 816 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 512 篇 工学
    • 344 篇 计算机科学与技术...
    • 300 篇 软件工程
    • 121 篇 生物工程
    • 80 篇 信息与通信工程
    • 70 篇 生物医学工程(可授...
    • 67 篇 控制科学与工程
    • 56 篇 光学工程
    • 55 篇 电气工程
    • 48 篇 化学工程与技术
    • 41 篇 电子科学与技术(可...
    • 26 篇 安全科学与工程
    • 20 篇 仪器科学与技术
    • 19 篇 机械工程
    • 17 篇 网络空间安全
    • 16 篇 力学(可授工学、理...
  • 379 篇 理学
    • 188 篇 数学
    • 125 篇 生物学
    • 121 篇 物理学
    • 82 篇 统计学(可授理学、...
    • 57 篇 化学
    • 39 篇 系统科学
    • 17 篇 地球物理学
  • 119 篇 管理学
    • 68 篇 管理科学与工程(可...
    • 52 篇 图书情报与档案管...
    • 37 篇 工商管理
  • 62 篇 医学
    • 52 篇 临床医学
    • 43 篇 基础医学(可授医学...
    • 25 篇 公共卫生与预防医...
    • 23 篇 药学(可授医学、理...
  • 19 篇 法学
    • 17 篇 社会学
  • 15 篇 经济学
  • 13 篇 农学
  • 7 篇 教育学

主题

  • 48 篇 machine learning
  • 47 篇 deep learning
  • 42 篇 accuracy
  • 22 篇 real-time system...
  • 22 篇 feature extracti...
  • 20 篇 predictive model...
  • 20 篇 reviews
  • 19 篇 training
  • 18 篇 convolutional ne...
  • 17 篇 reinforcement le...
  • 16 篇 medical services
  • 16 篇 decision making
  • 16 篇 artificial intel...
  • 16 篇 machine learning...
  • 15 篇 support vector m...
  • 15 篇 image segmentati...
  • 14 篇 diseases
  • 13 篇 forecasting
  • 11 篇 deep neural netw...
  • 11 篇 neural networks

机构

  • 49 篇 center for machi...
  • 31 篇 center for data ...
  • 30 篇 ai for science i...
  • 25 篇 school of mathem...
  • 25 篇 munich center fo...
  • 21 篇 beijing internat...
  • 20 篇 australian insti...
  • 18 篇 vector institute...
  • 14 篇 machine learning...
  • 13 篇 department of ar...
  • 13 篇 munich center fo...
  • 13 篇 center for machi...
  • 13 篇 munich data scie...
  • 12 篇 dp technology
  • 12 篇 machine learning...
  • 12 篇 machine learning...
  • 12 篇 departments of c...
  • 11 篇 department of ar...
  • 11 篇 peking universit...
  • 10 篇 national enginee...

作者

  • 30 篇 weinan e.
  • 22 篇 prateek verma
  • 21 篇 müller klaus-rob...
  • 18 篇 von lilienfeld o...
  • 16 篇 dong bin
  • 15 篇 schuller björn w...
  • 13 篇 krahmer felix
  • 13 篇 bin dong
  • 12 篇 aditya barhate
  • 12 篇 triantafyllopoul...
  • 11 篇 zhang linfeng
  • 11 篇 li zhang
  • 11 篇 montavon grégoir...
  • 11 篇 verma prateek
  • 10 篇 do thanh-toan
  • 10 篇 abhay tale
  • 10 篇 carneiro gustavo
  • 10 篇 von rudorff guid...
  • 9 篇 swapnil gundewar
  • 8 篇 jie zhao

语言

  • 543 篇 英文
  • 271 篇 其他
  • 1 篇 中文
检索条件"机构=Mathematical Institute for Machine Learning and Data Science"
816 条 记 录,以下是521-530 订阅
排序:
Empirical Macroeconomics and DSGE Modeling in Statistical Perspective
arXiv
收藏 引用
arXiv 2022年
作者: McDonald, Daniel J. Shalizi, Cosma Rohilla Department of Statistics University of British Columbia VancouverBC Canada Department of Statistics and Data Science and of Machine Learning Carnegie Mellon University PittsburghPA United States Santa Fe Institute Santa FeNM United States
Dynamic stochastic general equilibrium (DSGE) models have been an ubiquitous, and controversial, part of macroeconomics for decades. In this paper, we approach DSGEs purely as statstical models. We do this by applying... 详细信息
来源: 评论
High-speed and low-power molecular dynamics processing unit(MDPU)with ab initio accuracy
收藏 引用
npj Computational Materials 2024年 第1期10卷 559-568页
作者: Pinghui Mo Yujia Zhang Zhuoying Zhao Hanhan Sun Junhua Li Dawei Guan Xi Ding Xin Zhang Bo Chen Mengchao Shi Duo Zhang Denghui Lu Yinan Wang Jianxing Huang Fei Liu Xinyu Li Mohan Chen Jun Cheng Bin Liang Weinan E Jiayu Dai Linfeng Zhang Han Wang Jie Liu College of Integrated Circuits Hunan UniversityChangsha410082P.R.China College of Electrical and Information Engineering Hunan UniversityChangsha410082P.R.China College of Computer National University of Defense TechnologyChangsha410073P.R.China Department of Physics National University of Defense TechnologyChangsha410073P.R.China DP Technology 100080 BeijingP.R.China AI for Science Institute 100080 BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking University100871 BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking University100871 BeijingP.R.China School of Mathematical Science Peking University100871 BeijingP.R.China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEMCollege of Chemistry and Chemical EngineeringXiamen UniversityXiamen361005P.R.China School of Integrated Circuits Peking University100871 BeijingP.R.China Center for Machine Learning Research Peking University100871 BeijingP.R.China Institute of Applied Physics and Computational Mathematics 100088 BeijingP.R.China Greater Bay Area Institute for Innovation Hunan UniversityGuangzhou511300P.R.China Department of Electrical and Computer Engineering University of WashingtonSeattleWA98195USA
Molecular dynamics(MD)is an indispensable atomistic-scale computational tool widely-used in various *** the past decades,nearly all ab initio MD and machine-learning MD have been based on the general-purpose central/g... 详细信息
来源: 评论
Homophily and Incentive Effects in Use of Algorithms
arXiv
收藏 引用
arXiv 2022年
作者: Fogliato, Riccardo Fazelpour, Sina Gupta, Shantanu Lipton, Zachary Danks, David Department of Statistics and Data Science Carnegie Mellon University United States Department of Philosophy and Religion Khoury College of Computer Sciences Northeastern University United States Machine Learning Department Carnegie Mellon University United States Halicioğlu Data Science Institute Department of Philosophy University of California San Diego United States
As algorithmic tools increasingly aid experts in making consequential decisions, the need to understand the precise factors that mediate their influence has grown commensurately. In this paper, we present a crowdsourc... 详细信息
来源: 评论
Sentiment Analysis Using machine learning Methods
Sentiment Analysis Using Machine Learning Methods
收藏 引用
Intelligent & Innovative Practices in Engineering & Management (IIPEM), International Conference on
作者: Abhishek Badholia Tarun Dhar Diwan Preeti Narooka Pravin B Khatkale Ankit Vishnoi Keshav Kaushik Department of Data Science Shri Shankaracharya Institute of Professional Management and Technology Raipur Atal Bihari Vajpayee University Bilaspur India Artificial Intelligence and Machine Learning School of Computer and Engineering Manipal University Jaipur India Sanjivani University Kopargaon Maharashtra India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Amity School of Engineering and Technology Amity University Punjab Mohali India
machine learning (ML) will be utilized to evaluate sentiment analysis in this project. This study aims to do this. Sentiment analysis is a popular natural language processing area. This is a natural language processin... 详细信息
来源: 评论
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-Resolution
arXiv
收藏 引用
arXiv 2023年
作者: Wang, Yan Su, Tongtong Li, Yusen Cao, Jiuwen Wang, Gang Liu, Xiaoguang Nankai-Baidu Joint Lab School of Computer Science Nankai University Tianjin300350 China Tianjin Key Laboratory of Network and Data Security Technology Tianjin300071 China Machine Learning and I-health International Cooperation Base of Zhejiang Province and Artificial Intelligence Institute Hangzhou Dianzi University 300018 China
Recent research on deep convolutional neural networks (CNNs) has provided a significant performance boost on efficient super-resolution (SR) tasks by trading off the performance and applicability. However, most existi... 详细信息
来源: 评论
Regression with comparisons: escaping the curse of dimensionality with ordinal information
The Journal of Machine Learning Research
收藏 引用
The Journal of machine learning Research 2020年 第1期21卷 6480-6533页
作者: Yichong Xu Sivaraman Balakrishnan Aarti Singh Artur Dubrawski Machine Learning Department Department of Statistics and Data Science Machine Learning Department Auton Lab The Robotics Institute Carnegie Mellon University Pittsburgh PA
In supervised learning, we typically leverage a fully labeled dataset to design methods for function estimation or prediction. In many practical situations, we are able to obtain alternative feedback, possibly at a lo... 详细信息
来源: 评论
Alchemical insights into approximately quadratic energies of iso-electronic atoms
arXiv
收藏 引用
arXiv 2024年
作者: Krug, Simon León Anatole von Lilienfeld, O. Machine Learning Group Technische Universität Berlin Berlin10587 Germany Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany Chemical Physics Theory Group Department of Chemistry University of Toronto St. George Campus TorontoON Canada Department of Materials Science and Engineering University of Toronto St. George Campus TorontoON Canada Vector Institute for Artificial Intelligence TorontoON Canada Department of Physics University of Toronto St. George Campus TorontoON Canada Acceleration Consortium University of Toronto TorontoON Canada
Accurate quantum mechanics based predictions of property trends are so important for materials design and discovery that even inexpensive approximate methods are valuable. We use the Alchemical Integral Transform (AIT... 详细信息
来源: 评论
Condition Monitoring and Fault Diagnosis of BLDC Motor in Electric Vehicles Using Artificial Intelligence
Condition Monitoring and Fault Diagnosis of BLDC Motor in El...
收藏 引用
Artificial Intelligence in Education and Industry 4.0 (IDICAIEI), DMIHER International Conference on
作者: Swapnil Gundewar Meher Langote Swapna Kamble Prashant Kamble Artificial Intelligence and Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawangi Maharashtra India Artificial Intelligence and Data Science Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawangi Maharashtra India Department of Information Technology Yeshwantrao Chavan College of Engineering Nagpur Maharashtra India Department of Mechanical Technology Yeshwantrao Chavan College of Engineering Nagpur Maharashtra India
Due to their high benefits in terms of environment and standards of battery advancement, Electric Vehicles (EVs) are extremely important in the shift towards transportation. Here the Brushless DC (BLDC) motor is an in... 详细信息
来源: 评论
Active learning meets fractal decision boundaries: a cautionary tale from the Sitnikov three-body problem
arXiv
收藏 引用
arXiv 2023年
作者: Payot, Nicolas Pasquato, Mario Trani, Alessandro Alberto Hezaveh, Yashar Perreault-Levasseur, Laurence Département de Physique Université de Montréal Mila Quebec Artificial Intelligence Institute Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Canada Dipartimento di Fisica e Astronomia Università di Padova Vicolo dell’Osservatorio 5 PadovaI-35122 Italy Niels Bohr Institute Copenhagen Denmark Research Center for the Early Universe School of Science The University of Tokyo Tokyo Japan Okinawa Institute of Science and Technology Okinawa Japan
Chaotic systems such as the gravitational N-body problem are ubiquitous in astronomy. machine learning (ML) is increasingly deployed to predict the evolution of such systems, e.g. with the goal of speeding up simulati... 详细信息
来源: 评论
Add and thin: diffusion for temporal point processes  23
Add and thin: diffusion for temporal point processes
收藏 引用
Proceedings of the 37th International Conference on Neural Information Processing Systems
作者: David Lüdke Marin Biloš Olcksandr Shellur Marten Lienen Stephan Günnemann School of Computation Information and Technology Technical University of Munich Germany and Munich Data Science Institute Technical University of Munich Germany School of Computation Information and Technology Technical University of Munich Germany and Machine Learning Research Morgan Stanley School of Computation Information and Technology Technical University of Munich Germany and Amazon Web Services Germany
Autoregressive neural networks within the temporal point process (TPP) framework have become the standard for modeling continuous-time event data. Even though these models can expressively capture event sequences in a...
来源: 评论