咨询与建议

限定检索结果

文献类型

  • 214 篇 期刊文献
  • 69 篇 会议

馆藏范围

  • 283 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 194 篇 工学
    • 130 篇 计算机科学与技术...
    • 118 篇 软件工程
    • 60 篇 生物工程
    • 57 篇 生物医学工程(可授...
    • 41 篇 光学工程
    • 26 篇 信息与通信工程
    • 22 篇 电气工程
    • 22 篇 化学工程与技术
    • 19 篇 电子科学与技术(可...
    • 17 篇 控制科学与工程
    • 10 篇 仪器科学与技术
    • 7 篇 机械工程
    • 7 篇 动力工程及工程热...
    • 7 篇 安全科学与工程
    • 5 篇 土木工程
  • 150 篇 理学
    • 63 篇 数学
    • 62 篇 生物学
    • 60 篇 物理学
    • 32 篇 化学
    • 30 篇 统计学(可授理学、...
    • 7 篇 系统科学
  • 45 篇 管理学
    • 25 篇 管理科学与工程(可...
    • 21 篇 工商管理
    • 14 篇 图书情报与档案管...
  • 40 篇 医学
    • 33 篇 临床医学
    • 29 篇 基础医学(可授医学...
    • 16 篇 药学(可授医学、理...
    • 14 篇 公共卫生与预防医...
  • 8 篇 经济学
    • 8 篇 应用经济学
  • 7 篇 法学
    • 7 篇 社会学
  • 2 篇 教育学
  • 1 篇 农学
  • 1 篇 军事学

主题

  • 20 篇 machine learning
  • 10 篇 deep learning
  • 8 篇 image segmentati...
  • 7 篇 decision making
  • 6 篇 reinforcement le...
  • 6 篇 forecasting
  • 5 篇 benchmarking
  • 4 篇 deep neural netw...
  • 4 篇 graph neural net...
  • 4 篇 real-time system...
  • 4 篇 feature extracti...
  • 4 篇 diseases
  • 4 篇 accuracy
  • 3 篇 scalability
  • 3 篇 cancer
  • 3 篇 inverse problems
  • 3 篇 medical imaging
  • 3 篇 computational mo...
  • 3 篇 predictive model...
  • 3 篇 semantics

机构

  • 18 篇 vector institute...
  • 14 篇 machine learning...
  • 12 篇 machine learning...
  • 12 篇 machine learning...
  • 12 篇 departments of c...
  • 11 篇 center for machi...
  • 10 篇 center for data ...
  • 10 篇 department of ar...
  • 9 篇 national biomedi...
  • 9 篇 bifold – berlin ...
  • 7 篇 university of pe...
  • 7 篇 university kasse...
  • 7 篇 heidelberg
  • 6 篇 department of ra...
  • 6 篇 bifold berlin in...
  • 6 篇 berlin institute...
  • 6 篇 department of ph...
  • 6 篇 beijing internat...
  • 6 篇 department of ar...
  • 6 篇 data and web sci...

作者

  • 24 篇 müller klaus-rob...
  • 18 篇 von lilienfeld o...
  • 12 篇 triantafyllopoul...
  • 12 篇 montavon grégoir...
  • 11 篇 schuller björn w...
  • 10 篇 von rudorff guid...
  • 8 篇 li hongwei bran
  • 8 篇 bakas spyridon
  • 8 篇 de bruijne marle...
  • 7 篇 kofler florian
  • 7 篇 menze bjoern
  • 6 篇 khan danish
  • 6 篇 li zhang
  • 6 篇 ezhov ivan
  • 6 篇 linguraru marius...
  • 6 篇 roth benjamin
  • 6 篇 bin dong
  • 6 篇 keuper margret
  • 6 篇 eberle oliver
  • 5 篇 pfreundt franz-j...

语言

  • 267 篇 英文
  • 16 篇 其他
检索条件"机构=Biomedical Data Science and Machine Learning Group"
283 条 记 录,以下是131-140 订阅
排序:
XPASC: Measuring Generalization in Weak Supervision by Explainability and Association
arXiv
收藏 引用
arXiv 2022年
作者: März, Luisa Asgari, Ehsaneddin Braune, Fabienne Zimmermann, Franziska Roth, Benjamin Research Group Data Mining and Machine Learning Faculty of Computer Science University of Vienna Vienna Austria Faculty of Philological and Cultural Studies University of Vienna Vienna Austria AI Innovation & Pre-Development Data:Lab Volkswagen AG Munich Germany UniVie Docotoral School Computer Science Vienna Austria CAPE Analytics Mountain ViewCA United States
Weak supervision is leveraged in a wide range of domains and tasks due to its ability to create massive amounts of labeled data, requiring only little manual effort. Standard approaches use labeling functions to speci...
来源: 评论
Individual Fairness Through Reweighting and Tuning
arXiv
收藏 引用
arXiv 2024年
作者: Mahamadou, Abdoul Jalil Djiberou Goetz, Lea Altman, Russ Stanford Center for Biomedical Ethics Stanford University StanfordCA94305 United States Artificial Intelligence and Machine Learning GSK LondonN1C 4AG United Kingdom Department of Biomedical Data Science Stanford University StanfordCA94305 United States Department of Bioengineering Stanford University StanfordCA94305 United States Department of Genetics Stanford University StanfordCA94305 United States Department of Medicine Stanford University StanfordCA94305 United States
Inherent bias within society can be amplified and perpetuated by artificial intelligence (AI) systems. To address this issue, a wide range of solutions have been proposed to identify and mitigate bias and enforce fair... 详细信息
来源: 评论
RBGNet: Ray-based grouping for 3D Object Detection
arXiv
收藏 引用
arXiv 2022年
作者: Wang, Haiyang Shi, Shaoshuai Yang, Ze Fang, Rongyao Qian, Qi Li, Hongsheng Schiele, Bernt Wang, Liwei Center for Data Science Peking University China Max Planck Institute for Informatics Germany University of Toronto Canada The Chinese University of Hong Kong Hong Kong Alibaba Group China Key Laboratory of Machine Perception MOE School of Artificial Intelligence Peking University China International Center for Machine Learning Research Peking University China
As a fundamental problem in computer vision, 3D object detection is experiencing rapid growth. To extract the point-wise features from the irregularly and sparsely distributed points, previous methods usually take a f... 详细信息
来源: 评论
The Alchemical Integral Transform revisited
arXiv
收藏 引用
arXiv 2023年
作者: Krug, Simon León von Lilienfeld, O. Anatole 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
We recently introduced the Alchemical Integral Transform (AIT) enabling the prediction of energy differences, and guessed an Ansatz to parametrize space r in some alchemical change λ. Here, we present a rigorous deri... 详细信息
来源: 评论
A Review of machine learning Algorithms in Diabetes Management
A Review of Machine Learning Algorithms in Diabetes Manageme...
收藏 引用
Sentiment Analysis and Deep learning (ICSADL), International Conference on
作者: Unnati Gayaki Subodh Daronde Abhay Tale Aditya Barhate Department of Computer Science and Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Wardha Maharashtra India Department of Biomedical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (Deemed to be University)) Wardha Maharashtra India Department of Artificial Intelligence and Data Science Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Wardha Maharashtra India Department of Artificial Intelligence and Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Wardha Maharashtra India
Diabetes is a prevalent and chronic disease affecting millions worldwide, posing significant challenges in its management and treatment. This review article aims to explore the current and potential future roles of ma... 详细信息
来源: 评论
Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis
Overcoming Rare-Language Discrimination in Multi-Lingual Sen...
收藏 引用
IEEE International Conference on Big data
作者: Jasmin Lampert Christoph H. Lampert Competence Unit Data Science & Artificial Intelligence AIT Austrian Institute of Technology Vienna Austria Machine Learning and Computer Vision Group Institute of Science and Technology Austria (IST Austria) Klosterneuburg Austria
The digitalization of almost all aspects of our everyday lives has led to unprecedented amounts of data being freely available on the Internet. In particular social media platforms provide rich sources of user-generat... 详细信息
来源: 评论
Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence
arXiv
收藏 引用
arXiv 2022年
作者: Jafari, Mahboobeh Shoeibi, Afshin Ghassemi, Navid Heras, Jonathan Ling, Sai Ho Beheshti, Amin Zhang, Yu-Dong Wang, Shui-Hua Alizadehsani, Roohallah Gorriz, Juan M. Acharya, U. Rajendra Rokny, Hamid Alinejad Internship in BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia Data Science and Computational Intelligence Institute University of Granada Spain Department of Mathematics and Computer Science University of La Rioja La Rioja Spain Australia Data Analytics Lab Department of Computing Macquarie University SydneyNSW2109 Australia School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Deakin University VIC3217 Australia Department of Psychiatry University of Cambridge United Kingdom School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia UNSW Data Science Hub The University of New South Wales SydneyNSW2052 Australia Research Centre Macquarie University Sydney2109 Australia
Myocarditis is a significant cardiovascular disease (CVD) that poses a threat to the health of many individuals by causing damage to the myocardium. The occurrence of microbes and viruses, including the likes of HIV, ... 详细信息
来源: 评论
Flow-Based Sampling for Entanglement Entropy and the machine learning of Defects
收藏 引用
Physical Review Letters 2025年 第15期134卷 151601-151601页
作者: Andrea Bulgarelli Elia Cellini Karl Jansen Stefan Kühn Alessandro Nada Shinichi Nakajima Kim A. Nicoli Marco Panero Department of Physics University of Turin and INFN Turin unit Via Pietro Giuria 1 I-10125 Turin Italy Computation-Based Science and Technology Research Center The Cyprus Institute Nicosia Cyprus Deutsches Elektronen-Synchrotron DESY Zeuthen Germany Berlin Institute for the Foundations of Learning and Data (BIFOLD) Berlin Germany Machine Learning Group Technische Universität Berlin Berlin Germany RIKEN Center for AIP Tokyo Japan Transdisciplinary Research Area (TRA) Matter University of Bonn Germany Helmholtz Institute for Radiation and Nuclear Physics (HISKP) Bonn Germany Department of Physics and Helsinki Institute of Physics PL 64 FIN-00014 University of Helsinki Finland
We introduce a novel technique to numerically calculate Rényi entanglement entropies in lattice quantum field theory using generative models. We describe how flow-based approaches can be combined with the replica... 详细信息
来源: 评论
Calculated state-of-the art results for solvation and ionization energies of thousands of organic molecules relevant to battery design
arXiv
收藏 引用
arXiv 2024年
作者: Weinreich, Jan Karandashev, Konstantin Arrieta, Daniel Jose Arismendi Hermansson, Kersti Anatole von Lilienfeld, O. LausanneCH-1015 Switzerland University of Vienna Faculty of Physics Kolingasse 14-16 WienAT-1090 Austria Department of Chemistry-Ångström Laboratory Uppsala University Box 538 Uppsala75121 Sweden Vector Institute for Artificial Intelligence TorontoONM5S 1M1 Canada Departments of Chemistry Materials Science and Engineering and Physics University of Toronto St. George Campus TorontoON Canada Machine Learning Group Technische Universität Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany
We present high-quality reference data for two fundamentally important groups of molecular properties related to a compound's utility as a lithium battery electrolyte. The first one is energy changes associated wi... 详细信息
来源: 评论
Fetal Re-Identification in Multiple Pregnancy Ultrasound Images Using Deep learning
Fetal Re-Identification in Multiple Pregnancy Ultrasound Ima...
收藏 引用
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
作者: Elisabeth Gabler Michael Nissen Thomas R. Altstidl Adriana Titzmann Kai Packhäuser Andreas Maier Peter A. Fasching Bjoern M. Eskofier Heike Leutheuser Department Artificial Intelligence in Biomedical Engineering Machine Learning and Data Analytics (MaD) Lab Friedrich-Alexander-Universität Erlangen-Nurnberg (FAU) Erlangen Germany Department of Gynecology and Obstetrics Erlangen University Hospital Friedrich-Alexander-Universität Erlangen-Nurnberg (FAU) Erlangen Germany Department of Computer Science Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nurnberg (FAU) Erlangen Germany
Ultrasound examinations during pregnancy can detect abnormal fetal development, which is a leading cause of perinatal mortality. In multiple pregnancies, the position of the fetuses may change between examinations. Th...
来源: 评论