图 书 馆开课单位--曼彻斯特大学
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1Detecting 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
2A 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
3Chaos 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
4A 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
5Automating 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
6Bayesian 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
7Foresight 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
8Automating 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
9Variational 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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