| Directory > Computers > Artificial Intelligence > Neural Networks > People Frohlich, Jochen
Overview of neural networks, and explanation of Java classes that implement backpropagation, and
Kohonen feature maps.
http://rfhs8012.fh-regensburg.de/~saj39122/jfroehl/diplom/e-index.html
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Schein, Andrew I.
Machine learning approaches to data mining focussing on text mining applications.
http://www.cis.upenn.edu/~ais
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Chu, Selina
Artificial intelligence, machine learning, data mining.
http://www-scf.usc.edu/~selinach
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Fujita, Hajime
Partially observable markov decision processes (POMDP), reinforcement learning, multi-agent
systems.
http://hawaii.aist-nara.ac.jp/~hajime-f/
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Pearlmutter, Barak
Neural networks, machine learning, acoustic source seperation and localisation, independent
component analysis, brain imaging.
http://www-bcl.cs.may.ie/~barak/
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Joshi, Prashant
Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.
http://www.igi.tugraz.at/joshi
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Versace, Massimiliano
Neural networks applied to visual perception and computational modeling of mental disorders.
http://www.maxversace.com
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Garcia, Christophe
Computer vision, image analysis, neural networks.
http://www.csd.uoc.gr/~cgarcia
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Anthony, Martin
Computational learning theory, discrete mathematics.
http://www.maths.lse.ac.uk/Personal/martin/
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Andrieu, Christophe
Particle filtering and Monte Carlo Markov Chain methods.
http://www.stats.bris.ac.uk/~maxca/
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Agakov, Felix
Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and
causality.
http://www.inf.ed.ac.uk/people/staff/Felix_Agakov.html
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Bulsari, A.
Neural networks and nonlinear modelling for process engineering.
http://www.abo.fi/~abulsari
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Beal, Matthew J.
Bayesian inference, variational methods, graphical models.
http://www.cs.toronto.edu/~beal
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Wainwright, Martin
Statistical signal and image processing, natural image modelling, graphical models.
http://www.eecs.berkeley.edu/~martinw/
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Zhou, Zhi-Hua
Neural computing, data mining, evolutionary computing, ensemble networks.
http://cs.nju.edu.cn/people/zhouzh/
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Hughes, Nicholas
Automated Analysis of ECG.
http://www.robots.ox.ac.uk/~nph/
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Sykacek, Peter
Brain Computer Interface.
http://www.robots.ox.ac.uk/~psyk/
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Murray-Smith, Roderick
Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent
interfaces.
http://www.dcs.gla.ac.uk/~rod/
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Mika, Sebastian
Machine learning and explorative data analysis: support vector machines, kernel principal component
analysis and kernel Fisher discriminant analysis.
http://ida.first.gmd.de/homepages/mika/
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Xing, Eric
Statistical learning, machine learning approaches to computational biology, pattern recognition and
control.
http://www.cs.berkeley.edu/~epxing/
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Russell, Stuart
Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.
http://www.cs.berkeley.edu/~russell/
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Hopfield, John J.
Neural networks, collective behaviour of systems of simple processors. Most noted for Hopfield
networks.
http://neuron.princeton.edu/~john/
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Lawrence, Neil
Probabilistic models, variational methods.
http://www.dcs.shef.ac.uk/~neil
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Dietterich, Thomas G.
Reinforcement learning, machine learning, supervised learning.
http://cs.oregonstate.edu/~tgd/
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Bengio, Samy
Torch machine learning library, including SVMTorch support vector machine program. Research on
mixture models, hidden markov models, multimodal fusion, speaker verification.
http://www.idiap.ch/~bengio/index_en.html
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Tipping, Mike
Bayesian learning, relevance vector machine, probabilistic principal component analysis.
http://research.microsoft.com/users/mtipping/pages/mtipping.htm
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Friedman, Nir
Learning of probabilistic models, applications to computational biology.
http://www.cs.huji.ac.il/~nir/
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Muresan, Raul C.
Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.
http://www.raulmuresan.home.ro/
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de Garis, Hugo
Evolvable neural network models, neural networks for programmable hardware, large neural networks.
http://www.cs.usu.edu/~degaris/
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Joseph Wakeling's Neural Systems Research Page
Research papers and information on biologically inspired neural networks, brain modelling, AI and
related topics. A cross-disciplinary site mixing information from physics, neuroscience, cognitive
science and other fields.
http://neuro.webdrake.net/
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Williams, Christopher K. I.
Gaussian processes, image interpretation, graphical models, pattern recognition.
http://www.dai.ed.ac.uk/homes/ckiw/
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Weiss, Yair
Vision, Bayesian methods, neural computation.
http://www.cs.huji.ac.il/~yweiss/
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Smola, Alex J.
Kernel methods for prediction and data analysis.
http://mlg.anu.edu.au/~smola/
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MacKay, David
Bayesian theory and inference, error-correcting codes, machine learning.
http://www.inference.phy.cam.ac.uk/mackay/
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Kawato, Mitsuo
Computational neuroscience, neural network modelling.
http://www.isd.atr.co.jp/~kawato/
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Hinton, Geoffrey E.
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of
back-propagation.
http://www.cs.toronto.edu/~hinton/
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Frey, Brendan J.
Iterative decoding, unsupervised learning, graphical models.
http://www.psi.utoronto.ca/~frey/
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Cottrell, Garrison W.
An artrificial intelligence researcher who is an expert on neural networks.
http://charlotte.ucsd.edu/~gary/
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Bishop, Chris
Graphical models, variational methods, pattern recognition.
http://research.microsoft.com/~cmbishop/
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Appl, Martin
Reinforcement learning, soft-computing, optimization.
http://www.planet-interkom.de/martin.barbara/martin.html
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Attias, Hagai
Graphical models, variational Bayes, independent factor analysis.
http://research.microsoft.com/~hagaia/
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Roberts, Stephen
Machine learning and medical data analysis, independent component analysis and information theory.
http://www.robots.ox.ac.uk/~sjrob/
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Herbrich, Ralph
Statistical learning theory, support vector machines and kernel methods.
http://www.research.microsoft.com/users/rherb/
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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.
http://eivind.imm.dtu.dk/staff/winther/
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Bach, Francis
Machine learning, kernel methods, kernel independent component analysis and graphical models
http://www.cs.berkeley.edu/~fbach/
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Minka, Thomas P.
Machine learning, computer vision, Bayesian methods.
http://www.stat.cmu.edu/~minka/
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Coolen, Ton
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
http://www.mth.kcl.ac.uk/~tcoolen/
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Roweis, Sam T.
Speech processing, auditory scene analysis, machine learning.
http://www.cs.toronto.edu/~roweis/
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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.
http://www.anc.ed.ac.uk/~amos/
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Kearns, Michael
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
http://www.cis.upenn.edu/~mkearns/
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LeCun, Yann
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
http://yann.lecun.com/
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Saul, Lawrence K.
Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
http://www.cis.upenn.edu/~lsaul/
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de Freitas, Nando
Bayesian inference, Markov chain Monte Carlo simulation, machine learning.
http://www.cs.ubc.ca/~nando/
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Rovetta, Stefano
Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data
analysis/industrial automation/information retrieval. Teaching activities.
http://www.disi.unige.it/person/RovettaS/
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Tishby, Naftali
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and
cognitive science.
http://www.cs.huji.ac.il/~tishby/
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Heskes, Tom
Learning and generalization in neural networks.
http://www.mbfys.kun.nl/mbfys/people/tom/
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Wiegerinck, Wim
Inference in graphical models, mean field and variational approaches.
http://www.mbfys.kun.nl/mbfys/people/wimw/
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Lerner, Uri N.
Hybrid and Bayesian networks.
http://robotics.Stanford.EDU/~uri
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Koller, Daphne
Probabilistic models for complex uncertain domains.
http://robotics.stanford.edu/~koller/
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Rao, Rajesh P. N.
Models of human and computer vision.
http://www.cs.washington.edu/homes/rao/
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Keysers, Daniel
Pattern recognition and statistical modelling for object recognition.
http://www-i6.Informatik.RWTH-Aachen.DE/~keysers/
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Wunsch II, Donald C.
Reinforcement Learning, Adaptive Critic Designs, Control, Optimization, Graph Theory,
Bioinformatics, Intrusion Detection.
http://www.ece.umr.edu/~dwunsch/
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Dovzhenko, Alexander Yu.
Neural networks for computer clusters, oscillations in neural networks
http://www.itp.ac.ru/~alex/
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Wallis, Guy
Object recognition, cognitive neuroscience, interaction between vision and motor movements.
http://www.uq.edu.au/~uqgwalli/
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Welling, Max
Unsupervised learning, probabilistic density estimation, machine vision.
http://www.cs.utoronto.ca/~welling
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Kali, Szabolcs
Learning and memory in the brain, hippocampus.
http://www.gatsby.ucl.ac.uk/~szabolcs
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Kakade, Sham
Reinforcement learning and conditioning, mathematical models of neural processing.
http://www.gatsby.ucl.ac.uk/~sham
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Morris, Quaid
Machine learning for medical diagnosis and biological data analysis.
http://www.gatsby.ucl.ac.uk/~quaid
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Paccanaro, Alberto
Learning distributed representation of concepts from relational data.
http://www.gatsby.ucl.ac.uk/~alberto/
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Brown, Andrew
Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
http://www.gatsby.ucl.ac.uk/~andy
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Sallans, Brian
Decision making under uncertainty, reinforcement learning, unsupervised learning.
http://www.gatsby.ucl.ac.uk/~sallans
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Lawrence, Steve
Information dissemination and retrieval, machine learning and neural networks.
http://www.neci.nj.nec.com/homepages/lawrence/
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Rasmussen, Carl Edward
Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.
http://www.gatsby.ucl.ac.uk/~edward
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Wu, Yingnian
Stochastic generative models for complex visual phenomena.
http://www.stat.ucla.edu/~ywu/
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Zhu, Song Chun
Vision and graphics, statistical modelling and computing, neural computation.
http://www.cis.ohio-state.edu/~szhu/
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Yedidia, Jonathan S.
Statistical methods for inference and learning.
http://www.merl.com/people/yedidia/
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Opper, Manfred
Statistical physics, information theory and applied probability and applications to machien
learning and complex systems.
http://www.ncrg.aston.ac.uk/People/opperm/
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Kappen, Bert
Boltzmann machines, computational neurobiology, online learning.
http://www.mbfys.kun.nl/mbfys/people/bert/
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Simard, Patrice
Machine learning and generalization.
http://www.research.microsoft.com/~patrice/
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Phillips, Jonathon
Face recognition.
http://www.itl.nist.gov/iaui/894.03/staff/jonathon.html
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Wiskott, Laurenz
Face recognition, Invariances in learning and vision.
http://itb.biologie.hu-berlin.de/~wiskott/homepage.html
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Caruana, Rich
Multitask learning.
http://www.cs.cmu.edu/~caruana/
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Meila, Marina
Graphical models, learning in high dimensions, tree networks.
http://www.stat.washington.edu/mmp/
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Pathegama, Mahinda
Intelligent information systems, physiological sciences systems.
http://www.kes.unisa.edu.au/~mahinda/index.htm
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Boutilier, Craig
Decision making and planning under uncertainty, reinforcement learning, game theory and economic
models.
http://www.cs.toronto.edu/~cebly/
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Zemel, Richard
Unsupervised learning, machine learning, computational models of neural processing.
http://www.cs.utoronto.ca/~zemel/
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Ng, Andrew
Reinforcement learning, machine learning.
http://www.cs.berkeley.edu/~ang/
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Saund, Eric
Intermediate level structure in vision.
http://www.parc.xerox.com/spl/members/saund/
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Lafferty, John D.
Statistical machine learning, text and natural language processing, information retrieval,
information theory.
http://www.cs.cmu.edu/afs/cs.cmu.edu/user/lafferty/www/homepage.html
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Olshausen, Bruno
Visual coding, statistics of images, independent components analysis.
http://redwood.ucdavis.edu/bruno/
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Shuurmans, Dale
Computational learning, complex probability modelling.
http://www.lpaig.uwaterloo.ca:80/~dale/
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McCallum, Andrew
Machine learning, text and information retrieval and extraction, reinforcement learning.
http://www.cs.cmu.edu/~mccallum/
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Teh, Yee Whye
Learning and inference in complex probabilistic models.
http://www.cs.utoronto.ca/~ywteh
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Saad, David
Neural computing, error-correcting codes and cryptography using statistical and statistical
mechanics techniques.
http://www.ncrg.aston.ac.uk/People/saadd
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de Sa, Virginia
Supervised and unsupervised learning, cross-modal learning.
http://keck.ucsf.edu/~desa/
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Beveridge, Ross
Computer vision, model-based object recognition, face recognition.
http://www.cs.colostate.edu/~ross/
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Sutton, Richard S.
Reinforcement learning.
http://www-anw.cs.umass.edu/~rich/sutton.html
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Honavar, Vasant
Constructive learning, computational learning theory, spatial learning, cognitive modelling,
incremental learning.
http://www.cs.iastate.edu/~honavar/
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Calvin, William H.
Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.
http://faculty.washington.edu/wcalvin/
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Bartlett, Marian Stewart
Image analysis with unsupervised learning, face recognition, facial expression analysis.
http://ergo.ucsd.edu/~marni/
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Seung, Sebastian
Short-term memory, learning and memory in the brain, computational learning theory.
http://hebb.mit.edu/people/seung/
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Sahani, Maneesh
Statistical analysis of neural data, experimental design in neuroscience.
http://www.gatsby.ucl.ac.uk/~maneesh/
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Revow, Michael
Hand-written character recognition.
http://www.cs.toronto.edu/~revow/
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Schetinin, Vitaly
Biomedical data mining, diagnostic rule extraction and quality control in industry using a variety
of techniques.
http://nnlab.tripod.com
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Murphy, Kevin P.
Graphical models, machine learning, reinforcement learning.
http://www.cs.berkeley.edu/~murphyk
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Li, Zhaoping
Non-linear neural dynamics, visual segmentation, sensory processing.
http://www.gatsby.ucl.ac.uk/~zhaoping
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Leow, Wee Kheng
Computer vision, computational olfaction.
http://www.comp.nus.edu.sg/~leowwk
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Leen, Todd
Online learning, machine learning, learning dynamics.
http://www.cse.ogi.edu/~tleen
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Oja, Erkki
Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.
http://www.cis.hut.fi/oja/
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Murray, Alan
Neural networks and VLSI hardware.
http://www.ee.ed.ac.uk/~afm/
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Jensen, Finn Verner
Graphical models, belief propagation.
http://www.cs.auc.dk/~fvj
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Jaakkola, Tommi S.
Graphical models, variational methods, kernel methods.
http://www.ai.mit.edu/people/tommi
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Ghahramani, Zoubin
Sensorimotor control, unsupervised learning, probabilistic machine learning.
http://www.gatsby.ucl.ac.uk/~zoubin
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Freeman, William T.
Bayesian perception, computer vision, image processing.
http://www.merl.com/people/freeman
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Ballard, Dana H.
Visual perception with neural networks.
http://www.cs.rochester.edu/users/faculty/dana
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Amari, Shun-ichi
Neural network learning, information geometry.
http://www.islab.brain.riken.go.jp/~amari/
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Dayan , Peter
Representation and learning in neural processing systems, unsupervised learning, reinforcement
learning.
http://www.gatsby.ucl.ac.uk/~dayan/
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Brody, Carlos D.
Somatosensory working memory, computation with action potentials, design of complex stimuli for
sensory neurophysiology.
http://www.cns.caltech.edu/~carlos/
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Adelson, Edward T.
Visual perception, machine vision, image processing.
http://www-bcs.mit.edu/people/adelson/
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Neal, Radford
Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data
compression.
http://www.cs.toronto.edu/~radford
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Maass, Wolfgang
Theory of computation, computation in spiking neurons.
http://www.cis.tu-graz.ac.at/igi/maass/
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Sejnowski, Terry
Sensory representation in visual cortex, memory representation and adaptive organization of
visuo-motor transformations.
http://www.salk.edu/faculty/sejnowski.html
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Jordan, Michael I.
Graphical models, variational methods, machine learning, reasoning under uncertainty.
http://www.cs.berkeley.edu/~jordan/
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Becker, Sue
Neural network models of learning and memory, computational neuroscience, unsupervised learning in
perceptual systems.
http://www.science.mcmaster.ca/Psychology/sb.html
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