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检索条件"机构=Biomedical Data Science and Machine Learning Group"
286 条 记 录,以下是231-240 订阅
排序:
Evolutionary Monte Carlo of QM properties in chemical space: Electrolyte design
arXiv
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arXiv 2023年
作者: Karandashev, Konstantin Weinreich, Jan Heinen, Stefan Arrieta, Daniel Jose Arismendi von Rudorff, Guido Falk Hermansson, Kersti von Lilienfeld, O. Anatole University of Vienna Faculty of Physics Kolingasse 14-16 WienAT-1090 Austria Vector Institute for Artificial Intelligence TorontoONM5S 1M1 Canada Department of Chemistry-Angström Laboratory Uppsala University Box 538 UppsalaSE-75121 Sweden University Kassel Department of Chemistry Heinrich-Plett-Str.40 Kassel34132 Germany Heinrich-Plett-Strase 40 Kassel34132 Germany 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
Optimizing a target function over the space of organic molecules is an important problem appearing in many fields of applied science, but also a very difficult one due to the vast number of possible molecular systems.... 详细信息
来源: 评论
Towards deployment-centric multimodal AI beyond vision and language
arXiv
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arXiv 2025年
作者: Liu, Xianyuan Zhang, Jiayang Zhou, Shuo van der Plas, Thijs L. Vijayaraghavan, Avish Grishina, Anastasiia Zhuang, Mengdie Schofield, Daniel Tomlinson, Christopher Wang, Yuhan Li, Ruizhe van Zeeland, Louisa Tabakhi, Sina Demeocq, Cyndie Li, Xiang Das, Arunav Timmerman, Orlando Baldwin-McDonald, Thomas Wu, Jinge Bai, Peizhen Al Sahili, Zahraa Alwazzan, Omnia Do, Thao N. Suvon, Mohammod N.I. Wang, Angeline Cipolina-Kun, Lucia Moretti, Luigi A. Farndale, Lucas Jain, Nitisha Efremova, Natalia Ge, Yan Varela, Marta Lam, Hak-Keung Celiktutan, Oya Evans, Ben R. Coca-Castro, Alejandro Wu, Honghan Abdallah, Zahraa S. Chen, Chen Danchev, Valentin Tkachenko, Nataliya Lu, Lei Zhu, Tingting Slabaugh, Gregory G. Moore, Roger K. Cheung, William K. Charlton, Peter H. Lu, Haiping Centre for Machine Intelligence University of Sheffield Sheffield United Kingdom School of Computer Science University of Sheffield Sheffield United Kingdom The Alan Turing Institute London United Kingdom Department of Metabolism Digestion and Reproduction Imperial College London London United Kingdom Department of Applied AI Simula Research Laboratory Oslo Norway Information School University of Sheffield Sheffield United Kingdom NHS England Leeds United Kingdom Institute of Health Informatics University College London London United Kingdom Department of Engineering King’s College London London United Kingdom Department of Computing Science University of Aberdeen Aberdeen United Kingdom School of Informatics University of Edinburgh Edinburgh United Kingdom School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Department of Informatics King’s College London London United Kingdom Department of Earth Sciences University of Cambridge Cambridge United Kingdom Department of Computer Science University of Manchester Manchester United Kingdom Department of Computer Science Queen Mary University of London London United Kingdom Digital Environment Research Institute Queen Mary University of London London United Kingdom Department of Computer Science University of Bath Bath United Kingdom Department of Classics King’s College London London United Kingdom School of Electrical Electronic and Mechanical Engineering University of Bristol Bristol United Kingdom School of Engineering University of the West of England Bristol United Kingdom Cancer Research UK Scotland Institute Glasgow United Kingdom School of Business and Management Queen Mary University of London London United Kingdom City St George’s University of London London United Kingdom British Antarctic Survey Cambridge United Kingdom School of Health and Wellbeing University of Glasgow Glasgow United Kingdom Chief Data & AI Office Lloyds Banking Group Lo
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as healthcare, science, and engineering. ... 详细信息
来源: 评论
T-Cell Receptor Optimization with Reinforcement learning and Mutation Policies for Precision Immunotherapy
arXiv
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arXiv 2023年
作者: Chen, Ziqi Min, Martin Renqiang Guo, Hongyu Cheng, Chao Clancy, Trevor Ning, Xia Computer Science and Engineering The Ohio State University ColumbusOH43210 United States Machine Learning Department NEC Labs PrincetonNJ08540 United States Digital Technologies Research Centre National Research Council Canada ON Canada Department of Medicine Baylor College of Medicine HoustonTX77030 United States NEC Oncolmmunity AS Oslo Cancer Cluster Innovation Park Ullernchausséen 64 Oslo0379 Norway Biomedical Informatics The Ohio State University ColumbusOH43210 United States Translational Data Analytics Institute The Ohio State University ColumbusOH43210 United States
T cells monitor the health status of cells by identifying foreign peptides displayed on their surface. T-cell receptors (TCRs), which are protein complexes found on the surface of T cells, are able to bind to these pe... 详细信息
来源: 评论
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
arXiv
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arXiv 2024年
作者: Bassi, Pedro R.A.S. Li, Wenxuan Tang, Yucheng Isensee, Fabian Wang, Zifu Chen, Jieneng Chou, Yu-Cheng Roy, Saikat Kirchhoff, Yannick Rokuss, Maximilian Huang, Ziyan Ye, Jin He, Junjun Wald, Tassilo Ulrich, Constantin Baumgartner, Michael Maier-Hein, Klaus H. Jaeger, Paul Ye, Yiwen Xie, Yutong Zhang, Jianpeng Chen, Ziyang Xia, Yong Xing, Zhaohu Zhu, Lei Sadegheih, Yousef Bozorgpour, Afshin Kumari, Pratibha Azad, Reza Merhof, Dorit Shi, Pengcheng Ma, Ting Du, Yuxin Bai, Fan Huang, Tiejun Zhao, Bo Wang, Haonan Li, Xiaomeng Gu, Hanxue Dong, Haoyu Yang, Jichen Mazurowski, Maciej A. Gupta, Saumya Wu, Linshan Zhuang, Jiaxin Chen, Hao Roth, Holger Xu, Daguang Blaschko, Matthew B. Decherchi, Sergio Cavalli, Andrea Yuille, Alan L. Zhou, Zongwei Department of Computer Science Johns Hopkins University United States Department of Pharmacy and Biotechnology University of Bologna Italy Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Italy NVIDIA United States Germany Germany ESAT-PSI KU Leuven Belgium Faculty of Mathematics and Computer Science Heidelberg University Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Germany Shanghai Jiao Tong University China Shanghai Artificial Intelligence Laboratory China Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany DKFZ Germany School of Computer Science and Engineering Northwestern Polytechnical University China Australian Institute for Machine Learning The University of Adelaide Australia College of Computer Science and Technology Zhejiang University China Hong Kong University of Science and Technology Guangzhou China Hong Kong University of Science and Technology Hong Kong Faculty of Informatics and Data Science University of Regensburg Germany Faculty of Electrical Engineering and Information Technology RWTH Aachen University Germany Fraunhofer Institute for Digital Medicine MEVIS Germany Electronic & Information Engineering School Harbin Institute of Technology Shenzhen China China The Chinese University of Hong Kong Hong Kong Peking University China Department of Electrical and Computer Engineering Duke University United States Stony Brook University United States Department of Computer Science and Engineering Department of Chemical and Biological Engineering Division of Life Science Hong Kong University of Science and Technology Hong Kong Data Science and Computation Facility Fondazione Istituto Italiano di Tecnologia Italy Ecole Polytechnique Fédérale de Lausanne Switzerland
How can we test AI performance? This question seems trivial, but it isn’t. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and sho... 详细信息
来源: 评论
Advanced Process Control in Manufacturing Using IoT Devices and Artificial Neural Networks
Advanced Process Control in Manufacturing Using IoT Devices ...
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Sustainable Expert Systems (ICSES), International Conference on
作者: V. Sumathi Ramesh S Chethan Chandra S Basavaraddi Visumathi J Ishwarya M.V S. Srinivasan Department of Mathematics Sri Sairam Engineering College Chennai Tamil Nadu India Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Artificial Intelligence and Machine Learning R&D Don Bosco Institute of Technology VTU Belagavi Karnataka India Department of Information Technology Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Artificial intelligence and Data science Department Agni College of Technology Chennai Tamil Nadu India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India
Optimization of industrial activities is significantly helped by Advanced Process Control (APC), which increases efficiency, decreases costs, and improves product quality. Artificial Neural Networks (ANNs) and the Int... 详细信息
来源: 评论
Insightful analysis of historical sources at scales beyond human capabilities using unsupervised machine learning and XAI
arXiv
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arXiv 2023年
作者: Eberle, Oliver Büttner, Jochen El-Hajj, Hassan Montavon, Grégoire Müller, Klaus-Robert Valleriani, Matteo Machine Learning Group Technische Universität Berlin Marchstr. 23 Berlin10587 Germany BIFOLD – Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany Max Planck Institute for the History of Science Boltzmannstr. 22 Berlin14195 Germany Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 14 Berlin14195 Germany Department of Artificial Intelligence Korea University Seoul136-713 Korea Republic of Max Planck Institute for Informatics Stuhlsatzenhausweg 4 Saarbrücken66123 Germany Institute of History and Philosophy of Science Technology and Literature Faculty I - Humanities and Educational Sciences Technische Universität Berlin Straße des 17. Juni 135 Berlin10623 Germany The Cohn Institute for the History and Philosophy of Science and Ideas Faculty of Humanities Tel Aviv University P.O.B. 39040 Ramat Aviv Tel Aviv6139001 Israel
Historical materials are abundant. Yet, piecing together how human knowledge has evolved and spread both diachronically and synchronically remains a challenge that can so far only be very selectively addressed. The va... 详细信息
来源: 评论
Roaming leads to amino acid photodamage: A deep learning study of tyrosine
arXiv
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arXiv 2021年
作者: Westermayr, Julia Gastegger, Michael Vörös, Dora Panzenboeck, Lisa Joerg, Florian González, Leticia Marquetand, Philipp University of Warwick Department of Chemistry Gibbet Hill Rd CoventryCV4 7AL United Kingdom Technical University of Berlin Machine Learning Group Berlin10587 Germany University of Vienna Faculty of Chemistry Institute of Theoretical Chemistry Währinger Str. 17 Vienna1090 Austria University of Vienna Vienna Research Platform on Accelerating Photoreaction Discovery Währinger Str. 17 Vienna1090 Austria University of Vienna Faculty of Chemistry Data Science @ Uni Vienna Währinger Str. 29 Vienna1090 Austria
Although the amino acid tyrosine is among the main building blocks of life, its photochemistry is not fully understood. Traditional theoretical simulations are neither accurate enough, nor computationally efficient to... 详细信息
来源: 评论
Confidence intervals uncovered: Are we ready for real-world medical imaging AI?
arXiv
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arXiv 2024年
作者: Christodoulou, Evangelia Reinke, Annika Houhou, Rola Kalinowski, Piotr Erkan, Selen Sudre, Carole H. Burgos, Ninon Boutaj, Sofiène Loizillon, Sophie Solal, Maëlys Rieke, Nicola Cheplygina, Veronika Antonelli, Michela Mayer, Leon D. Tizabi, Minu D. Jorge Cardoso, M. Simpson, Amber Jäger, Paul F. Kopp-Schneider, Annette Varoquaux, Gaël Colliot, Olivier Maier-Hein, Lena Heidelberg Div. Intelligent Medical Systems Germany AI Health Innovation Cluster Germany NCT Heidelberg a partnership between DKFZ Heidelberg University Hospital Germany DKFZ Heidelberg Helmholtz Imaging Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Germany DKFZ Heidelberg Interactive Machine Learning Group Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London United Kingdom Sorbonne Université Institut du Cerveau - Paris Brain Institute - ICM CNRS Inria Inserm AP-HP Hôpital de la Pitié-Salpêtrière France NVIDIA Germany Department of Computer Science IT University of Copenhagen Denmark Centre for Medical Image Computing University College London United Kingdom School of Computing Queen’s University Canada Department of Biomedical and Molecular Sciences Queen’s University Canada Division of Biostatistics DKFZ Germany Parietal project team INRIA Saclay-Île de France France Faculty of Mathematics and Computer Science Heidelberg University Germany Medical Faculty Heidelberg University Germany
Medical imaging is spearheading the AI transformation of healthcare. Performance reporting is key to determine which methods should be translated into clinical practice. Frequently, broad conclusions are simply derive... 详细信息
来源: 评论
Author Correction: Efficient interatomic descriptors for accurate machine learning force fields of extended molecules
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Nature communications 2023年 第1期14卷 4116页
作者: Adil Kabylda Valentin Vassilev-Galindo Stefan Chmiela Igor Poltavsky Alexandre Tkatchenko Department of Physics and Materials Science University of Luxembourg L-1511 Luxembourg City Luxembourg. Machine Learning Group Technische Universität Berlin 10587 Berlin Germany. BIFOLD - Berlin Institute for the Foundations of Learning and Data 10587 Berlin Germany. Department of Physics and Materials Science University of Luxembourg L-1511 Luxembourg City Luxembourg. alexandre.tkatchenko@uni.lu.
来源: 评论
Alchemical harmonic approximation based potential for iso-electronic diatomics: Foundational baseline for ∆-machine learning
arXiv
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arXiv 2024年
作者: Krug, Simon León Khan, Danish von Lilienfeld, O. Anatole Machine Learning Group Technische Universität Berlin Berlin Charlottenburg 10587 Germany Vector Institute for Artificial Intelligence TorontoONM5S 1M1 Canada Department of Chemistry University of Toronto St. George campus TorontoONM5S 3H6 Canada Berlin Institute for the Foundations of Learning and Data Charlottenburg Berlin10587 Germany Acceleration Consortium University of Toronto 80 St George St TorontoONM5S 3H6 Canada Department of Materials Science and Engineering University of Toronto St. George campus TorontoONM5S 3E4 Canada Department of Physics University of Toronto St. George campus TorontoONM5S 1A7 Canada
We introduce the alchemical harmonic approximation (AHA) of the absolute electronic energy for charge-neutral iso-electronic diatomics at fixed interatomic distance d0. To account for variations in distance, we combin... 详细信息
来源: 评论