图 书 馆开课单位--柏林工业大学
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21Towards an Estimate of the Neural Information of the BOLD Signal[向一个估计的神经信息的大胆的信号]
Felix Bießmann(柏林工业大学) The blood oxygen level dependent (BOLD) signal as measured by functional magnetic resonance imaging (fMRI) has become a standard marker of neural acti...
热度：40
Felix Bießmann(柏林工业大学) The blood oxygen level dependent (BOLD) signal as measured by functional magnetic resonance imaging (fMRI) has become a standard marker of neural acti...
热度：40
22Welcome and Overview of the Workshop on Machine Learning Open Source[欢迎和机器学习开源研讨会概述]
Sören Sonnenburg, Mikio Braun(柏林工业大学)
热度：32
Sören Sonnenburg, Mikio Braun(柏林工业大学)
热度：32
2324Microscopic Simulation of Tsunami-Related Evacuation of the City of Padang[巴东市海啸疏散的微观模拟]
Kai Nagel(柏林工业大学) The evacuation of whole cities or even regions is an important problem, as demonstrated by recent events such as the evacuation of Houston in the case...
热度：47
Kai Nagel(柏林工业大学) The evacuation of whole cities or even regions is an important problem, as demonstrated by recent events such as the evacuation of Houston in the case...
热度：47
25Approximate inference for continuous time Markov processes[连续时间马尔可夫过程的近似推理]
Manfred Opper(柏林工业大学) Continuous time Markov processes (such as jump processes and diffusions) play an important role in the modelling of dynamical systems in many scientif...
热度：29
Manfred Opper(柏林工业大学) Continuous time Markov processes (such as jump processes and diffusions) play an important role in the modelling of dynamical systems in many scientif...
热度：29
26Shogun[将军]
Sören Sonnenburg(柏林工业大学) The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic ...
热度：35
Sören Sonnenburg(柏林工业大学) The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic ...
热度：35
27Perturbative Corrections to Expectation Consistent Approximate Inference[预期传递的扰乱性修正]
Manfred Opper(柏林工业大学) Algorithms for approximate inference usually come without any guarantee for the quality of the approximation. Nevertheless, we often find cases where ...
热度：29
Manfred Opper(柏林工业大学) Algorithms for approximate inference usually come without any guarantee for the quality of the approximation. Nevertheless, we often find cases where ...
热度：29
28Inverse Methods for EEG and MEG Source Reconstruction[脑电和脑磁图源重构的逆方法]
Guido Nolte, Stefan Haufe(柏林工业大学) In this lecture we review the most popular inverse methods for EEG and MEG source reconstruction. Inverse methods can be divided into three different ...
热度：102
Guido Nolte, Stefan Haufe(柏林工业大学) In this lecture we review the most popular inverse methods for EEG and MEG source reconstruction. Inverse methods can be divided into three different ...
热度：102
29Bernstein Focus: Neurotechnology Berlin[伯恩斯坦焦点：柏林神经科技]
Klaus-Robert Müller, John-Dylan Haynes, Sebastian Möller(柏林工业大学) The Bernstein Focus: Neurotechnology Berlin (BFNT-B) posits that neuroscientific results can be exploited for developing robust ‘real-world&rsqu...
热度：44
Klaus-Robert Müller, John-Dylan Haynes, Sebastian Möller(柏林工业大学) The Bernstein Focus: Neurotechnology Berlin (BFNT-B) posits that neuroscientific results can be exploited for developing robust ‘real-world&rsqu...
热度：44
30Probabilistic and Bayesian Modelling II[概率和贝叶斯建模II]
Manfred Opper(柏林工业大学) There is a dramatic growth in the availability of complex data from a wide range of different applications. The challenge of the data analyzer is to e...
热度：38
Manfred Opper(柏林工业大学) There is a dramatic growth in the availability of complex data from a wide range of different applications. The challenge of the data analyzer is to e...
热度：38