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Home: Artificial Intelligence: Neural Networks: People: Page 4
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- Storkey, 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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- Teh, Yee Whye
Learning and inference in complex probabilistic models.
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- Tipping, Mike
Bayesian learning, relevance vector machine, probabilistic principal component analysis.
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- Tishby, Naftali
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.
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- Tong, Simon
Machine learning, active learning, graphical models, support vector machines.
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- Wainwright, Martin
Statistical signal and image processing, natural image modelling, graphical models.
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- Wallis, Guy
Object recognition, cognitive neuroscience, interaction between vision and motor movements.
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- Welling, Max
Unsupervised learning, probabilistic density estimation, machine vision.
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- Wiegerinck, Wim
Inference in graphical models, mean field and variational approaches.
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- Winther, Ole
Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.
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- Wu, Yingnian
Stochastic generative models for complex visual phenomena.
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- Wunsch II, Donald C.
Reinforcement Learning, Adaptive Critic Designs, Control, Optimization, Graph Theory, Bioinformatics, Intrusion Detection.
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- Zemel, Richard
Unsupervised learning, machine learning, computational models of neural processing.
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- Zhu, Song Chun
Vision and graphics, statistical modelling and computing, neural computation.
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Pages: [<<] 1 2 3 4
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