开课单位--曼彻斯特大学
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Detecting Influences of Ontology Design Patterns in Biomedical Ontologies[检测生物医学本体中本体设计模式的影响]
Christian Kindermann(曼彻斯特大学) Detecting Influences of Ontology Design Patterns in Biomedical Ontologies
热度:28
Christian Kindermann(曼彻斯特大学) Detecting Influences of Ontology Design Patterns in Biomedical Ontologies
热度:28
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A Sentiment-labelled Corpus of Hansard Parliamentary Debate Speeches[议会议事录辩论演讲集]
Gavin Abercrombie(曼彻斯特大学) Hansard transcripts provide access to the opinions of MPs on many important issues, but are rather difficult for people to effectively process. Existi...
热度:55
Gavin Abercrombie(曼彻斯特大学) Hansard transcripts provide access to the opinions of MPs on many important issues, but are rather difficult for people to effectively process. Existi...
热度:55
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Chaos and Stability in Learning Random Two-person Games[随机二人对策学习中的混沌与稳定性]
Tobias Galla(曼彻斯特大学) Game theory often assumes perfect rationality. All agents know all payoff structures. They assume their opponents play fully rationally. Outcomes: Nas...
热度:34
Tobias Galla(曼彻斯特大学) Game theory often assumes perfect rationality. All agents know all payoff structures. They assume their opponents play fully rationally. Outcomes: Nas...
热度:34
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A snapshot of the OWL Web[猫头鹰网络的快照]
Nicolas Matentzoglu(曼彻斯特大学) Tool development for and empirical experimentation in OWL ontology engineering require a wide variety of suitable ontologies as input for testing and ...
热度:70
Nicolas Matentzoglu(曼彻斯特大学) Tool development for and empirical experimentation in OWL ontology engineering require a wide variety of suitable ontologies as input for testing and ...
热度:70
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Automating Biology Using Robot Scientists[利用机器人科学家实现生物自动化]
Ross D. King(曼彻斯特大学) Computer systems that can directly and accurately answer peoples’ questions over a broad domain of human knowledge have been envisioned by scien...
热度:33
Ross D. King(曼彻斯特大学) Computer systems that can directly and accurately answer peoples’ questions over a broad domain of human knowledge have been envisioned by scien...
热度:33
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Bayesian Gaussian process latent variable model[贝叶斯高斯过程潜在变量模型]
Michalis K. Titsias(曼彻斯特大学) We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensio...
热度:121
Michalis K. Titsias(曼彻斯特大学) We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensio...
热度:121
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Foresight methodology & Commonly used methods[有远见的方法和常用的方法]
Ozcan Saritas(曼彻斯特大学) Foresight methodology & Commonly used methods.
热度:42
Ozcan Saritas(曼彻斯特大学) Foresight methodology & Commonly used methods.
热度:42
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Automating Biology Using Robot Scientists[利用机器人科学家的自动化生物学]
Ross D. King(曼彻斯特大学) A robot scientist is a physically implemented robotic system that applies techniques from artificial intelligence to execute cycles of automated scien...
热度:58
Ross D. King(曼彻斯特大学) A robot scientist is a physically implemented robotic system that applies techniques from artificial intelligence to execute cycles of automated scien...
热度:58
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Variational Model Selection for Sparse Gaussian Process Regression[稀疏高斯过程回归变分模型的选择]
Michalis K. Titsias(曼彻斯特大学) Model selection for sparse Gaussian process (GP) models is an important problem that involves the selection of both the inducing/active variables and ...
热度:221
Michalis K. Titsias(曼彻斯特大学) Model selection for sparse Gaussian process (GP) models is an important problem that involves the selection of both the inducing/active variables and ...
热度:221
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