Subdirectories of People:
Categories related to Computers: Artificial Intelligence: Neural Networks: People: Computers: Artificial Intelligence: People (194) Science: Social Sciences: Psychology: Cognitive: People (125) Websites on People: 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. 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. Bartlett, Marian Stewart Image analysis with unsupervised learning, face recognition, facial expression analysis. 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. Brody, Carlos D. Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology. 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. Chu, Selina Artificial intelligence, machine learning, data mining. Coolen, Ton Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks. Cottrell, Garrison W. An artrificial intelligence researcher who is an expert on neural networks. Dahlem, Markus A. Neural network models of visual cortex to model neurological symptoms of migraine. 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 Garis, Hugo Evolvable neural network models, neural networks for programmable hardware, large neural networks. 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 multi-user 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. Frohlich, Jochen Overview of neural networks, and explanation of Java classes that implement backpropagation, and Kohonen feature maps. Garcia, Christophe Computer vision, image analysis, neural networks. Ghahramani, Zoubin Sensorimotor control, unsupervised learning, probabilistic machine learning. Hansen, Lars Kai Neural network ensembles, adaptive systems and applications in neuroinformatics. Herbrich, Ralph Statistical learning theory, support vector machines and kernel methods. 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. Hughes, Nicholas Automated Analysis of ECG. Jaakkola, Tommi S. Graphical models, variational methods, kernel methods. Jensen, Finn Verner Graphical models, belief propagation. Jordan, Michael I. Graphical models, variational methods, machine learning, reasoning under uncertainty. Joshi, Prashant Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons. 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. Lawrence, Neil Probabilistic models, variational methods. Lawrence, Steve Information dissemination and retrieval, machine learning and neural networks. LeCun, Yann Handwritten recognition, convolutional networks, image compression. Noted for LeNet. Leen, Todd Online learning, machine learning, learning dynamics. 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, Alan Neural networks and VLSI hardware. 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. Olier, Ivan Artificial intelligence, generative topographic map, missing data. Olshausen, Bruno Visual coding, statistics of images, independent components analysis. Opper, Manfred Statistical physics, information theory and applied probability and applications to machine learning and complex systems. 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. Prashant, Joshi Computational neuroscientist, with main areas of research interest being computational motor control, computational models of olfaction, computation with spiking neurons, neurocomputational basis of working memory and decision making, learning in biologically realistic circuits. 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. Revow, Michael Hand-written 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. Saad, David Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques. Sahani, Maneesh Statistical analysis of neural data, experimental design in neuroscience. Sallans, Brian Decision making under uncertainty, reinforcement learning, unsupervised learning. Saul, Lawrence K. Machine learning, pattern recognition, neural networks, voice processing, auditory computation. Saund, Eric Intermediate level structure in vision. Schein, Andrew I. Machine learning approaches to data mining focussing on text mining applications. Sejnowski, Terry Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations. Seung, Sebastian Short-term memory, learning and memory in the brain, computational learning theory. Shkolnik, Alexander Neurally controlled robotics. Shuurmans, Dale Computational learning, complex probability modelling. Simard, Patrice Machine learning and generalization. Smola, Alex J. Kernel methods for prediction and data analysis. Storkey, Amos Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks. Sutton, Richard S. Reinforcement learning. Sykacek, Peter Brain Computer Interface. Teh, Yee Whye Learning and inference in complex probabilistic models. 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. 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. Wiskott, Laurenz Face recognition, Invariances in learning and vision. Wu, Yingnian Stochastic generative models for complex visual phenomena. Xing, Eric Statistical learning, machine learning approaches to computational biology, pattern recognition and control. Yedidia, Jonathan S. Statistical methods for inference and learning. 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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