### Subcategories 1

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### Sites 78

Adelson, Edward T.

Visual perception, machine vision, image processing.

Allan, Moray

Computer vision, probabilistic models for image sequences, invariant features.

Amari, Shun-ichi

Neural network learning, information geometry.

Andonie, Razvan

Data structures for computational intelligence.

Andrieu, Christophe

Particle filtering and Monte Carlo Markov Chain methods.

Anthony, Martin

Computational learning theory, discrete mathematics.

Bach, Francis

Machine learning, kernel methods, kernel independent component analysis and graphical models

Beal, Matthew J.

Bayesian inference, variational methods, graphical models, nonparametric Bayes.

Becker, Sue

Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.

Beveridge, Ross

Computer vision, model-based object recognition, face recognition.

Bishop, Chris

Graphical models, variational methods, pattern recognition.

Boutilier, Craig

Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.

Brown, Andrew

Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.

Bulsari, A.

Neural networks and nonlinear modelling for process engineering.

Calvin, William H.

Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.

Caruana, Rich

Multitask learning.

Coolen, Ton

Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.

Dayan , Peter

Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.

de Freitas, Nando

Bayesian inference, Markov chain Monte Carlo simulation, machine learning.

De vito, Saverio

Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures

Dietterich, Thomas G.

Reinforcement learning, machine learning, supervised learning.

Dr Hooman Shadnia

Dedicated to artificial neural networks and their applications in medical research and computational chemistry. Offers a quick tutorial on theory on ANNs written in Persian.

Freeman, William T.

Bayesian perception, computer vision, image processing.

Frey, Brendan J.

Iterative decoding, unsupervised learning, graphical models.

Friedman, Nir

Learning of probabilistic models, applications to computational biology.

Grangier, David

Research focusing on Machine Learning, Neural Networks, Kernel Machines, Computer Vision and Speech Processing.

Hansen, Lars Kai

Neural network ensembles, adaptive systems and applications in neuroinformatics.

Heskes, Tom

Learning and generalization in neural networks.

Hinton, Geoffrey E.

Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.

Honavar, Vasant

Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning, causal inference, knowledge representation, preference reasoning.

Hughes, Nicholas

Automated Analysis of ECG.

Jaakkola, Tommi S.

Graphical models, variational methods, kernel methods.

Jordan, Michael I.

Graphical models, variational methods, machine learning, reasoning under uncertainty.

Kearns, Michael

Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.

Koller, Daphne

Probabilistic models for complex uncertain domains.

Lafferty, John D.

Statistical machine learning, text and natural language processing, information retrieval, information theory.

LeCun, Yann

Handwritten recognition, convolutional networks, image compression. Noted for LeNet.

Leow, Wee Kheng

Computer vision, computational olfaction.

Lerner, Uri N.

Hybrid and Bayesian networks.

Li, Zhaoping

Non-linear neural dynamics, visual segmentation, sensory processing.

Maass, Wolfgang

Theory of computation, computation in spiking neurons.

MacKay, David

Bayesian theory and inference, error-correcting codes, machine learning.

Malchiodi, Dario

Machine learning, Learning from uncertain data.

McCallum, Andrew

Machine learning, text and information retrieval and extraction, reinforcement learning.

Meila, Marina

Graphical models, learning in high dimensions, tree networks.

Minka, Thomas P.

Machine learning, computer vision, Bayesian methods.

Muresan, Raul C.

Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.

Murphy, Kevin P.

Graphical models, machine learning, reinforcement learning.

Murray-Smith, Roderick

Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.

Neal, Radford

Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.

Oja, Erkki

Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.

Olshausen, Bruno

Visual coding, statistics of images, independent components analysis.

Paccanaro, Alberto

Learning distributed representation of concepts from relational data.

Pearlmutter, Barak

Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.

Peterson, Leif E.

Researcher at Methodist Hospital Research Institute on classification technology and related fields.

Prashant, Joshi

Computational Neuroscientist. Research interests: reservoir computing, computational motor control, computation with spiking neurons.

Rao, Rajesh P. N.

Models of human and computer vision.

Rasmussen, Carl Edward

Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.

Roberts, Stephen

Machine learning and medical data analysis, independent component analysis and information theory.

Rovetta, Stefano

Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.

Roweis, Sam T.

Speech processing, auditory scene analysis, machine learning.

Russell, Stuart

Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.

Rutkowski, Leszek

Neural networks, fuzzy systems, computational intelligence.

Saul, Lawrence K.

Machine learning, pattern recognition, neural networks, voice processing, auditory computation.

Storkey, Amos

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

Tipping, Mike

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

Tishby, Naftali

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

Versace, Massimiliano

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

Wainwright, Martin

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

Wallis, Guy

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

Weiss, Yair

Vision, Bayesian methods, neural computation.

Williams, Christopher K. I.

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

Winther, Ole

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

Wu, Yingnian

Stochastic generative models for complex visual phenomena.

Xiaoguang, Rui

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

Xing, Eric

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

Zemel, Richard

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

Zhou, Zhi-Hua

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

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May 17, 2016 at 21:33:03 UTC
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