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Minsky, Marvin (12)

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Adelson, Edward T. - http://web.mit.edu/persci/people/adelson/
Visual perception, machine vision, image processing.

Allan, Moray - http://www.morayallan.com/
Computer vision, probabilistic models for image sequences, invariant features.

Amari, Shun-ichi - http://www.brain.riken.jp/labs/mns/amari/home-E.html
Neural network learning, information geometry.

Andonie, Razvan - http://www.cwu.edu/~andonie/
Data structures for computational intelligence.

Andrieu, Christophe - http://www.stats.bris.ac.uk/~maxca/
Particle filtering and Monte Carlo Markov Chain methods.

Anthony, Martin - http://www.maths.lse.ac.uk/Personal/martin/
Computational learning theory, discrete mathematics.

Attias, Hagai - http://research.goldenmetallic.com/
Graphical models, variational Bayes, independent factor analysis.

Bach, Francis - http://www.di.ens.fr/~fbach/
Machine learning, kernel methods, kernel independent component analysis and graphical models

Ballard, Dana H. - http://www.cs.rochester.edu/users/faculty/dana
Visual perception with neural networks.

Bartlett, Marian Stewart - http://ergo.ucsd.edu/~marni/
Image analysis with unsupervised learning, face recognition, facial expression analysis.

Beal, Matthew J. - http://www.cse.buffalo.edu/faculty/mbeal
Bayesian inference, variational methods, graphical models, nonparametric Bayes.

Becker, Sue - http://www.science.mcmaster.ca/Psychology/sb.html
Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.

Beveridge, Ross - http://www.cs.colostate.edu/~ross/
Computer vision, model-based object recognition, face recognition.

Bishop, Chris - http://research.microsoft.com/~cmbishop/
Graphical models, variational methods, pattern recognition.

Boutilier, Craig - http://www.cs.toronto.edu/~cebly/
Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.

Brody, Carlos D. - http://www.cshl.edu/public/SCIENCE/brody.html
Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology.

Brown, Andrew - http://www.ecs.soton.ac.uk/people/adb
Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.

Bulsari, A. - http://www.abo.fi/~abulsari
Neural networks and nonlinear modelling for process engineering.

Calvin, William H. - http://faculty.washington.edu/wcalvin/
Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.

Caruana, Rich - http://www.cs.cmu.edu/~caruana/
Multitask learning.

Cheung, Vincent - http://www.psi.toronto.edu/~vincent/
Machine learning and probabilistic graphical models for computer vision and computational molecular biology.

Chu, Selina - http://www-scf.usc.edu/~selinach
Artificial intelligence, machine learning, data mining.

Coolen, Ton - http://www.mth.kcl.ac.uk/~tcoolen/
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.

Cottrell, Garrison W. - http://charlotte.ucsd.edu/~gary/
An artificial intelligence researcher who is an expert on neural networks.

Dahlem, Markus A. - http://www.migraine-aura.org/EN/Markus_Dahlem.html
Neural network models of visual cortex to model neurological symptoms of migraine.

Dayan , Peter - http://www.gatsby.ucl.ac.uk/~dayan/
Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.

de Freitas, Nando - http://www.cs.ubc.ca/~nando/
Bayesian inference, Markov chain Monte Carlo simulation, machine learning.

de Garis, Hugo - http://www.iss.whu.edu.cn/degaris/
Evolvable neural network models, neural networks for programmable hardware, large neural networks.

De vito, Saverio - http://www.afs.enea.it/devito/
Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures

De Wilde, Philippe - http://www.macs.hw.ac.uk/~pdw/
Brain inspired models of uncertainty, linguistic and fuzzy uncertainty, uncertainty in dynamic multi-user environments.

Dietterich, Thomas G. - http://cs.oregonstate.edu/~tgd/
Reinforcement learning, machine learning, supervised learning.

Dr Hooman Shadnia - http://www.shadnia.com
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. - http://people.csail.mit.edu/billf/wtf.html
Bayesian perception, computer vision, image processing.

Frey, Brendan J. - http://www.psi.utoronto.ca/~frey/
Iterative decoding, unsupervised learning, graphical models.

Friedman, Nir - http://www.cs.huji.ac.il/~nir/
Learning of probabilistic models, applications to computational biology.

Frohlich, Jochen - http://rfhs8012.fh-regensburg.de/~saj39122/jfroehl/diplom/e-index.html
Overview of neural networks, and explanation of Java classes that implement backpropagation, and Kohonen feature maps.

Garcia, Christophe - http://www.csd.uoc.gr/~cgarcia
Computer vision, image analysis, neural networks.

Ghahramani, Zoubin - http://www.gatsby.ucl.ac.uk/~zoubin
Sensorimotor control, unsupervised learning, probabilistic machine learning.

Hansen, Lars Kai - http://eivind.imm.dtu.dk/staff/lkhansen/lkhansen.html
Neural network ensembles, adaptive systems and applications in neuroinformatics.

Herbrich, Ralph - http://www.research.microsoft.com/users/rherb/
Statistical learning theory, support vector machines and kernel methods.

Heskes, Tom - http://www.cs.ru.nl/~tomh/
Learning and generalization in neural networks.

Hinton, Geoffrey E. - http://www.cs.toronto.edu/~hinton/
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.

Honavar, Vasant - http://www.cs.iastate.edu/~honavar/
Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.

Hughes, Nicholas - http://www.robots.ox.ac.uk/~nph/
Automated Analysis of ECG.

Jaakkola, Tommi S. - http://www.ai.mit.edu/people/tommi
Graphical models, variational methods, kernel methods.

Jensen, Finn Verner - http://www.cs.auc.dk/~fvj
Graphical models, belief propagation.

Jordan, Michael I. - http://www.cs.berkeley.edu/~jordan/
Graphical models, variational methods, machine learning, reasoning under uncertainty.

Joshi, Prashant - http://www.igi.tugraz.at/joshi
Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.

Kearns, Michael - http://www.cis.upenn.edu/~mkearns/
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.

Koller, Daphne - http://ai.stanford.edu/~koller/
Probabilistic models for complex uncertain domains.

Lafferty, John D. - http://www.cs.cmu.edu/~lafferty/
Statistical machine learning, text and natural language processing, information retrieval, information theory.

Lawrence, Neil - http://www.dcs.shef.ac.uk/~neil
Probabilistic models, variational methods.

Lawrence, Steve - http://labs.google.com/people/lawrence/
Information dissemination and retrieval, machine learning and neural networks.

LeCun, Yann - http://yann.lecun.com/
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.

Leen, Todd - http://www.cse.ogi.edu/~tleen
Online learning, machine learning, learning dynamics.

Leow, Wee Kheng - http://www.comp.nus.edu.sg/~leowwk
Computer vision, computational olfaction.

Lerner, Uri N. - http://ai.stanford.edu/~uri/
Hybrid and Bayesian networks.

Li, Zhaoping - http://www.gatsby.ucl.ac.uk/~zhaoping/
Non-linear neural dynamics, visual segmentation, sensory processing.

Maass, Wolfgang - http://www.igi.tugraz.at/maass/
Theory of computation, computation in spiking neurons.

MacKay, David - http://www.inference.phy.cam.ac.uk/mackay/
Bayesian theory and inference, error-correcting codes, machine learning.

Malchiodi, Dario - http://homes.dsi.unimi.it/~malchiod/
Machine learning, Learning from uncertain data.

McCallum, Andrew - http://www.cs.umass.edu/~mccallum/
Machine learning, text and information retrieval and extraction, reinforcement learning.

Meila, Marina - http://www.stat.washington.edu/mmp/
Graphical models, learning in high dimensions, tree networks.

Minka, Thomas P. - http://research.microsoft.com/~minka/
Machine learning, computer vision, Bayesian methods.

Muresan, Raul C. - http://www.raulmuresan.home.ro/
Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.

Murphy, Kevin P. - http://www.cs.berkeley.edu/~murphyk
Graphical models, machine learning, reinforcement learning.

Murray-Smith, Roderick - http://www.dcs.gla.ac.uk/~rod/
Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.

Murray, Alan - http://www.ee.ed.ac.uk/~afm/
Neural networks and VLSI hardware.

Neal, Radford - http://www.cs.toronto.edu/~radford
Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.

Oja, Erkki - http://www.cis.hut.fi/oja/
Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.

Olier, Ivan - http://www.lsi.upc.edu/~iaolier/
Artificial intelligence, generative topographic map, missing data.

Olshausen, Bruno - https://redwood.berkeley.edu/bruno/
Visual coding, statistics of images, independent components analysis.

Opper, Manfred - http://www.ncrg.aston.ac.uk/People/opperm/Welcome.html
Statistical physics, information theory and applied probability and applications to machine learning and complex systems.

Paccanaro, Alberto - http://homes.gersteinlab.org/people/alberto/
Learning distributed representation of concepts from relational data.

Pearlmutter, Barak - http://www-bcl.cs.may.ie/~barak/
Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.

Rao, Rajesh P. N. - http://www.cs.washington.edu/homes/rao/
Models of human and computer vision.

Rasmussen, Carl Edward - http://learning.eng.cam.ac.uk/carl/
Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.

Revow, Michael - http://www.cs.toronto.edu/~revow/
Hand-written character recognition.

Roberts, Stephen - http://www.robots.ox.ac.uk/~sjrob/
Machine learning and medical data analysis, independent component analysis and information theory.

Rovetta, Stefano - http://www.disi.unige.it/person/RovettaS/
Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.

Roweis, Sam T. - http://www.cs.toronto.edu/~roweis/
Speech processing, auditory scene analysis, machine learning.

Russell, Stuart - http://www.cs.berkeley.edu/~russell/
Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.

Rutkowski, Leszek - http://www.kik.pcz.czest.pl/~rutkowski/
Neural networks, fuzzy systems, computational intelligence.

Saad, David - http://www.ncrg.aston.ac.uk/People/saadd/Welcome.html
Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques.

Sahani, Maneesh - http://www.gatsby.ucl.ac.uk/~maneesh/
Statistical analysis of neural data, experimental design in neuroscience.

Sallans, Brian - http://members.chello.at/hoebertz-sallans/sallans/index.html
Decision making under uncertainty, reinforcement learning, unsupervised learning.

Saul, Lawrence K. - http://www.cs.ucsd.edu/~saul/
Machine learning, pattern recognition, neural networks, voice processing, auditory computation.

Saund, Eric - http://www2.parc.com/spl/members/saund/
Intermediate level structure in vision.

Schein, Andrew I. - http://www.cis.upenn.edu/~ais
Machine learning approaches to data mining focussing on text mining applications.

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.

Seung, Sebastian - http://hebb.mit.edu/people/seung/
Short-term memory, learning and memory in the brain, computational learning theory.

Shkolnik, Alexander - http://web.mit.edu/shkolnik/www/
Neurally controlled robotics.

Shuurmans, Dale - http://www.lpaig.uwaterloo.ca/~dale/
Computational learning, complex probability modelling.

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.

Sutton, Richard S. - http://www-anw.cs.umass.edu/~rich/sutton.html
Reinforcement learning.

Sykacek, Peter - http://www.robots.ox.ac.uk/~psyk/
Brain Computer Interface.

Teh, Yee Whye - http://www.cs.utoronto.ca/~ywteh
Learning and inference in complex probabilistic models.

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.

Tishby, Naftali - http://www.cs.huji.ac.il/~tishby/
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.

Versace, Massimiliano - http://www.maxversace.com
Neural networks applied to visual perception and computational modeling of mental disorders.

Wainwright, Martin - http://www.eecs.berkeley.edu/~martinw/
Statistical signal and image processing, natural image modelling, graphical models.

Wallis, Guy - http://www.uq.edu.au/~uqgwalli/
Object recognition, cognitive neuroscience, interaction between vision and motor movements.

Weiss, Yair - http://www.cs.huji.ac.il/~yweiss/
Vision, Bayesian methods, neural computation.

Welling, Max - http://www.cs.utoronto.ca/~welling
Unsupervised learning, probabilistic density estimation, machine vision.

Williams, Christopher K. I. - http://www.dai.ed.ac.uk/homes/ckiw/
Gaussian processes, image interpretation, graphical models, pattern recognition.

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.

Wiskott, Laurenz - http://itb.biologie.hu-berlin.de/~wiskott/homepage.html
Face recognition, Invariances in learning and vision.

Wu, Yingnian - http://www.stat.ucla.edu/~ywu/
Stochastic generative models for complex visual phenomena.

Xing, Eric - http://www.cs.cmu.edu/~epxing/
Statistical learning, machine learning approaches to computational biology, pattern recognition and control.

Yedidia, Jonathan S. - http://www.merl.com/people/yedidia/
Statistical methods for inference and learning.

Zemel, Richard - http://www.cs.utoronto.ca/~zemel/
Unsupervised learning, machine learning, computational models of neural processing.

Zhou, Zhi-Hua - http://cs.nju.edu.cn/zhouzh/
Neural computing, data mining, evolutionary computing, ensemble networks.

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