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检索条件"机构=Biomedical Data Science and Machine Learning Group"
287 条 记 录,以下是191-200 订阅
排序:
Reinforcement learning in continuous time and space: a stochastic control approach
The Journal of Machine Learning Research
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The Journal of machine learning Research 2020年 第1期21卷 8145-8178页
作者: Haoran Wang Thaleia Zariphopoulou Xun Yu Zhou CAI Data Science and Machine Learning The Vanguard Group Inc. Malvern PA Department of Mathematics and IROM The University of Texas at Austin Austin TX and Oxford-Man Institute University of Oxford Oxford UK Department of Industrial Engineering and Operations Research The Data Science Institute Columbia University New York NY
We consider reinforcement learning (RL) in continuous time with continuous feature and action spaces. We motivate and devise an exploratory formulation for the feature dynamics that captures learning under exploration... 详细信息
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Accurate global machine learning force fields for molecules with hundreds of atoms
arXiv
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arXiv 2022年
作者: Chmiela, Stefan Vassilev-Galindo, Valentin Unke, Oliver T. Kabylda, Adil Sauceda, Huziel E. Tkatchenko, Alexandre Müller, Klaus-Robert Machine Learning Group Technische Universität Berlin Berlin10587 Germany Berlin Institute for the Foundations of Learning and Data – BIFOLD Germany Department of Physics and Materials Science University of Luxembourg Luxembourg CityL-1511 Luxembourg Google Research Brain Team Berlin Germany Departamento de Materia Condensada Instituto de Física Universidad Nacional Autónoma de México Cd. de MéxicoC.P. 04510 Mexico BASLEARN - TU Berlin BASF Joint Lab for Machine Learning Technische Universität Berlin Berlin10587 Germany Max Planck Institute for Informatics Stuhlsatzenhausweg Saarbrücken66123 Germany Department of Artificial Intelligence Korea University Anam-dong Seongbuk-gu Seoul02841 Korea Republic of
Global machine learning force fields (MLFFs), that have the capacity to capture collective many-atom interactions in molecular systems, currently only scale up to a few dozen atoms due a considerable growth of the mod... 详细信息
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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
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From quantum alchemy to Hammett's equation: Covalent bonding from atomic energy partitioning
arXiv
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arXiv 2022年
作者: Sahre, Michael J. von Rudorff, Guido Falk von Lilienfeld, O. Anatole University of Vienna Faculty of Physics Kolingasse 14-16 Vienna1090 Austria Währinger Str. 42 Vienna1090 Austria University Kassel Department of Chemistry Heinrich-Plett-Str.40 Kassel34132 Germany 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 an intuitive and general analytical approximation estimating the energy of covalent single and double bonds between participating atoms in terms of their respective nuclear charges with just three parameter... 详细信息
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Transformer-based normative modelling for anomaly detection of early schizophrenia
arXiv
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arXiv 2022年
作者: Da Costa, Pedro F. Dafflon, Jessica Mendes, Sergio Leonardo Sato, João Ricardo Jorge Cardoso, M. Leech, Robert Jones, Emily J.H. Pinaya, Walter H.L. Institute of Psychiatry Psychology & Neuroscience King’s College London United Kingdom Centre for Brain and Cognitive Development Birkbeck College London United Kingdom Data Science and Sharing Team National Institute of Mental Health BethesdaMD United States Machine Learning Team National Institute of Mental Health BethesdaMD United States Center of Mathematics Computing and Cognition Universidade Federal do ABC Brazil School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom
Despite the impact of psychiatric disorders on clinical health, early-stage diagnosis remains a challenge. machine learning studies have shown that classifiers tend to be overly narrow in the diagnosis prediction task... 详细信息
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Brain Imaging Generation with Latent Diffusion Models
arXiv
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arXiv 2022年
作者: Pinaya, Walter H.L. Tudosiu, Petru-Daniel Dafflon, Jessica Da Costa, Pedro F. Fernandez, Virginia Nachev, Parashkev Ourselin, Sebastien Cardoso, M. Jorge Department of Biomedical Engineering School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Data Science and Sharing Team Functional Magnetic Resonance Imaging Facility National Institute of Mental Health BethesdaMD20892 United States Machine Learning Team Functional Magnetic Resonance Imaging Facility National Institute of Mental Health BethesdaMD20892 United States Institute of Psychiatry Psychology & Neuroscience King’s College London United Kingdom Centre for Brain and Cognitive Development Birkbeck College United Kingdom Institute of Neurology University College London United Kingdom
Deep neural networks have brought remarkable breakthroughs in medical image analysis. However, due to their data-hungry nature, the modest dataset sizes in medical imaging projects might be hindering their full potent... 详细信息
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Encrypted machine learning of molecular quantum properties
arXiv
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arXiv 2022年
作者: Weinreich, Jan von Rudorff, Guido Falk von Lilienfeld, O. Anatole University of Vienna Faculty of Physics Kolingasse 14-16 WienAT-1090 Austria University of Vienna Vienna Doctoral School in Physics Boltzmanngasse 5 Vienna1090 Austria University Kassel Department of Chemistry Heinrich-Plett-Str.40 Kassel34132 Germany 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
Large machine learning models with improved predictions have become widely available in the chemical sciences. Unfortunately, these models do not protect the privacy necessary within commercial settings, prohibiting t... 详细信息
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The medical algorithmic audit (vol 4, pg e384, 2022)
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LANCET DIGITAL HEALTH 2022年 第6期4卷 E405-E405页
作者: Liu, X. Glocker, B. McCradden, M. M. Ghassemi, M. Denniston, A. K. Oakden-Rayner, L. Academic Unit of Ophthalmology Institute of Inflammation and Ageing College of Medical and Dental Sciences University of Birmingham UK Department of Ophthalmology University Hospitals Birmingham NHS Foundation Trust Birmingham UK Moorfields Eye Hospital NHS Foundation Trust London UK Health Data Research UK London UK Birmingham Health Partners Centre for Regulatory Science and Innovation University of Birmingham Birmingham UK Biomedical Image Analysis Group Department of Computing Imperial College London London UK The Hospital for Sick Children Toronto ON Canada Dalla Lana School of Public Health Toronto ON Canada Institute for Medical Engineering and Science and Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA National Institute of Health Research Biomedical Research Centre for Ophthalmology Moorfields Hospital London NHS Foundation Trust London UK University College London Institute of Ophthalmology London UK Australian Institute for Machine Learning University of Adelaide Adelaide SA Australia. lauren.oakden-rayner@adelaide.edu.au
Artificial intelligence systems for health care, like any other medical device, have the potential to fail. However, specific qualities of artificial intelligence systems, such as the tendency to learn spurious correl...
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learning with group Noise
arXiv
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arXiv 2021年
作者: Wang, Qizhou Yao, Jiangchao Gong, Chen Liu, Tongliang Gong, Mingming Yang, Hongxia Han, Bo Department of Computer Science Hong Kong Baptist University Hong Kong Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of MoE School of Computer Science and Engineering Nanjing University of Science and Technology China Data Analytics and Intelligence Lab Alibaba Group China Department of Computing Hong Kong Polytechnic University Hong Kong Trustworthy Machine Learning Lab School of Computer Science University of Sydney Australia School of Mathematics and Statistics University of Melbourne Australia
machine learning in the context of noise is a challenging but practical setting to plenty of real-world applications. Most of the previous approaches in this area focus on the pairwise relation (casual or correlationa... 详细信息
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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.
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