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the entire directory
only in Neural_Networks/People
Top
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Computers
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Artificial Intelligence
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Neural Networks
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People
(87)
Minsky, Marvin
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Computers: Artificial Intelligence: People
(135)
Science: Social Sciences: Psychology: Cognitive: People
(85)
Adelson, Edward T.
 Visual perception, machine vision, image processing.
Allan, Moray
 Computer vision, probabilistic models for image sequences, invariant features.
Amari, Shunichi
 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.
Attias, Hagai
 Graphical models, variational Bayes, independent factor analysis.
Bach, Francis
 Machine learning, kernel methods, kernel independent component analysis and graphical models
Ballard, Dana H.
 Visual perception with neural networks.
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, modelbased object recognition, face recognition.
Bishop, Chris
 Graphical models, variational methods, pattern recognition.
Bogaerts, Jan
 Blog about NLP using resonating neural networks.
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.
Cheung, Vincent
 Machine learning and probabilistic graphical models for computer vision and computational molecular biology.
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
De Wilde, Philippe
 Brain inspired models of uncertainty, linguistic and fuzzy uncertainty, uncertainty in dynamic multiuser environments.
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 coinventor of backpropagation.
Honavar, Vasant
 Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.
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
 Nonlinear neural dynamics, visual segmentation, sensory processing.
Maass, Wolfgang
 Theory of computation, computation in spiking neurons.
MacKay, David
 Bayesian theory and inference, errorcorrecting 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.
MurraySmith, 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, nonlinear Bayesian inference, evaluation and comparison of network models.
Revow, Michael
 Handwritten character recognition.
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.
Sejnowski, Terry
 Sensory representation in visual cortex, memory representation and adaptive organization of visuomotor transformations.
Seung, Sebastian
 Shortterm memory, learning and memory in the brain, computational learning theory.
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 humancomputer 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.
Welling, Max
 Unsupervised learning, probabilistic density estimation, machine vision.
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, ZhiHua
 Neural computing, data mining, evolutionary computing, ensemble networks.
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Last update: July 23, 2014 at 6:15:09 UTC 
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