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  Artificial Intelligence: Neural Networks: People

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Zhou, Zhi-Hua

http://cs.nju.edu.cn/zhouzh/

Neural computing, data mining, evolutionary computing, ensemble networks.

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Zemel, Richard

http://www.cs.utoronto.ca/~zemel/

Unsupervised learning, machine learning, computational models of neural processing.

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Xing, Eric

http://www.cs.cmu.edu/~epxing/

Statistical learning, machine learning approaches to computational biology, pattern recognition and control.

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Xiaoguang, Rui

http://sites.google.com/site/rxghome/

Researcher at University of Science and Technology of China. About image annotation, image retrieval, social network analysis, pattern recognition and machine learning.

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Wu, Yingnian

http://www.stat.ucla.edu/~ywu/

Stochastic generative models for complex visual phenomena.

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Winther, Ole

http://eivind.imm.dtu.dk/staff/winther/

Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.

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Williams, Christopher K. I.

http://www.dai.ed.ac.uk/homes/ckiw/

Gaussian processes, image interpretation, graphical models, pattern recognition.

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Welling, Max

http://www.cs.utoronto.ca/~welling

Unsupervised learning, probabilistic density estimation, machine vision.

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Weiss, Yair

http://www.cs.huji.ac.il/~yweiss/

Vision, Bayesian methods, neural computation.

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Wallis, Guy

http://www.uq.edu.au/~uqgwalli/

Object recognition, cognitive neuroscience, interaction between vision and motor movements.

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Wainwright, Martin

http://www.eecs.berkeley.edu/~martinw/

Statistical signal and image processing, natural image modelling, graphical models.

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Versace, Massimiliano

http://www.maxversace.com/

Neural networks applied to visual perception and computational modeling of mental disorders.

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Tishby, Naftali

http://www.cs.huji.ac.il/~tishby/

Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.

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Tipping, Mike

http://www.miketipping.com/

Varied machine learning and data analysis topics, including Bayesian inference, relevance vector machine, probabilistic principal component analysis and visualisation methods.

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Teh, Yee Whye

http://www.cs.utoronto.ca/~ywteh

Learning and inference in complex probabilistic models.

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Storkey, Amos

http://homepages.inf.ed.ac.uk/amos/

Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.

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Seung, Sebastian

http://hebb.mit.edu/people/seung/

Short-term memory, learning and memory in the brain, computational learning theory.

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Sejnowski, Terry

http://www.salk.edu/faculty/faculty_details.php?id=48

Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations.

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