Knowledge: people
See Also:
- computers → artificial intelligence → people
- science → social sciences → psychology → cognitive → people
Links
- Becker, Sue
http://www.science.mcmaster.ca/Psychology/sb.html - Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.
- Jordan, Michael I.
http://www.cs.berkeley.edu/~jordan/ - Graphical models, variational methods, machine learning, reasoning under uncertainty.
- Neal, Radford
http://www.cs.toronto.edu/~radford - Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.
- Adelson, Edward T.
http://www-bcs.mit.edu/people/adelson/ - Visual perception, machine vision, image processing.
- Dayan , Peter
http://www.gatsby.ucl.ac.uk/~dayan/ - Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.
- Ballard, Dana H.
http://www.cs.rochester.edu/users/faculty/dana - Visual perception with neural networks.
- Ghahramani, Zoubin
http://www.gatsby.ucl.ac.uk/~zoubin - Sensorimotor control, unsupervised learning, probabilistic machine learning.
- 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.
- Murray, Alan
http://www.ee.ed.ac.uk/~afm/ - Neural networks and VLSI hardware.
- Oja, Erkki
http://www.cis.hut.fi/oja/ - Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.
- 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.
- Li, Zhaoping
http://www.gatsby.ucl.ac.uk/~zhaoping - Non-linear neural dynamics, visual segmentation, sensory processing.
- Murphy, Kevin P.
http://www.cs.berkeley.edu/~murphyk - Graphical models, machine learning, reinforcement learning.
- Schetinin, Vitaly
http://nnlab.tripod.com - Biomedical data mining, diagnostic rule extraction and quality control in industry using a variety of techniques.
- Revow, Michael
http://www.cs.toronto.edu/~revow/ - Hand-written character recognition.
- Sahani, Maneesh
http://www.gatsby.ucl.ac.uk/~maneesh/ - Statistical analysis of neural data, experimental design in neuroscience.
- Seung, Sebastian
http://hebb.mit.edu/people/seung/ - Short-term memory, learning and memory in the brain, computational learning theory.
- Bartlett, Marian Stewart
http://ergo.ucsd.edu/~marni/ - Image analysis with unsupervised learning, face recognition, facial expression analysis.
- Calvin, William H.
http://faculty.washington.edu/wcalvin/ - Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.
- Honavar, Vasant
http://www.cs.iastate.edu/~honavar/ - Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.
- Sutton, Richard S.
http://www-anw.cs.umass.edu/~rich/sutton.html - Reinforcement learning.
- Beveridge, Ross
http://www.cs.colostate.edu/~ross/ - Computer vision, model-based object recognition, face recognition.
- Teh, Yee Whye
http://www.cs.utoronto.ca/~ywteh - Learning and inference in complex probabilistic models.
- Shuurmans, Dale
http://www.lpaig.uwaterloo.ca/~dale/ - Computational learning, complex probability modelling.
- Zemel, Richard
http://www.cs.utoronto.ca/~zemel/ - Unsupervised learning, machine learning, computational models of neural processing.
- Boutilier, Craig
http://www.cs.toronto.edu/~cebly/ - Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.
- Meila, Marina
http://www.stat.washington.edu/mmp/ - Graphical models, learning in high dimensions, tree networks.
- Caruana, Rich
http://www.cs.cmu.edu/~caruana/ - Multitask learning.
- Wiskott, Laurenz
http://itb.biologie.hu-berlin.de/~wiskott/homepage.html - Face recognition, Invariances in learning and vision.
- Simard, Patrice
http://www.research.microsoft.com/~patrice/ - Machine learning and generalization.
- Yedidia, Jonathan S.
http://www.merl.com/people/yedidia/ - Statistical methods for inference and learning.
- Wu, Yingnian
http://www.stat.ucla.edu/~ywu/ - Stochastic generative models for complex visual phenomena.
- Rasmussen, Carl Edward
http://www.gatsby.ucl.ac.uk/~edward - Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.
- Kakade, Sham
http://www.gatsby.ucl.ac.uk/~sham - Reinforcement learning and conditioning, mathematical models of neural processing.
- Kali, Szabolcs
http://www.gatsby.ucl.ac.uk/~szabolcs - Learning and memory in the brain, hippocampus.
- Welling, Max
http://www.cs.utoronto.ca/~welling - Unsupervised learning, probabilistic density estimation, machine vision.
- Wallis, Guy
http://www.uq.edu.au/~uqgwalli/ - Object recognition, cognitive neuroscience, interaction between vision and motor movements.
- Keysers, Daniel
http://www-i6.informatik.rwth-aachen.de/~keysers/ - Pattern recognition and statistical modelling for object recognition.
- Rao, Rajesh P. N.
http://www.cs.washington.edu/homes/rao/ - Models of human and computer vision.
- Tishby, Naftali
http://www.cs.huji.ac.il/~tishby/ - Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.
- 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.
- de Freitas, Nando
http://www.cs.ubc.ca/~nando/ - Bayesian inference, Markov chain Monte Carlo simulation, machine learning.
- LeCun, Yann
http://yann.lecun.com/ - Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
- Kearns, Michael
http://www.cis.upenn.edu/~mkearns/ - Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
- Storkey, Amos
http://www.anc.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.
- Roweis, Sam T.
http://www.cs.toronto.edu/~roweis/ - Speech processing, auditory scene analysis, machine learning.
- Coolen, Ton
http://www.mth.kcl.ac.uk/~tcoolen/ - Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
- 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.
- Herbrich, Ralph
http://www.research.microsoft.com/users/rherb/ - Statistical learning theory, support vector machines and kernel methods.
- Roberts, Stephen
http://www.robots.ox.ac.uk/~sjrob/ - Machine learning and medical data analysis, independent component analysis and information theory.
- Bishop, Chris
http://research.microsoft.com/~cmbishop/ - Graphical models, variational methods, pattern recognition.
- Cottrell, Garrison W.
http://charlotte.ucsd.edu/~gary/ - An artrificial intelligence researcher who is an expert on neural networks.
- Frey, Brendan J.
http://www.psi.utoronto.ca/~frey/ - Iterative decoding, unsupervised learning, graphical models.
- 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.
- MacKay, David
http://www.inference.phy.cam.ac.uk/mackay/ - Bayesian theory and inference, error-correcting codes, machine learning.
- Smola, Alex J.
http://mlg.anu.edu.au/~smola/ - Kernel methods for prediction and data analysis.
- Weiss, Yair
http://www.cs.huji.ac.il/~yweiss/ - Vision, Bayesian methods, neural computation.
- Williams, Christopher K. I.
http://www.dai.ed.ac.uk/homes/ckiw/ - Gaussian processes, image interpretation, graphical models, pattern recognition.
- Joseph Wakeling's Neural Systems Research Page
http://neuro.webdrake.net/ - 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.
- Friedman, Nir
http://www.cs.huji.ac.il/~nir/ - Learning of probabilistic models, applications to computational biology.
- Bengio, Samy
http://www.idiap.ch/~bengio/index_en.html - Torch machine learning library, including SVMTorch support vector machine program. Research on mixture models, hidden markov models, multimodal fusion, speaker verification.
- Dietterich, Thomas G.
http://cs.oregonstate.edu/~tgd/ - Reinforcement learning, machine learning, supervised learning.
- Lawrence, Neil
http://www.dcs.shef.ac.uk/~neil - Probabilistic models, variational methods.
- Russell, Stuart
http://www.cs.berkeley.edu/~russell/ - Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.
- Murray-Smith, Roderick
http://www.dcs.gla.ac.uk/~rod/ - Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.
- Sykacek, Peter
http://www.robots.ox.ac.uk/~psyk/ - Brain Computer Interface.
- Hughes, Nicholas
http://www.robots.ox.ac.uk/~nph/ - Automated Analysis of ECG.
- Wainwright, Martin
http://www.eecs.berkeley.edu/~martinw/ - Statistical signal and image processing, natural image modelling, graphical models.
- Bulsari, A.
http://www.abo.fi/~abulsari - Neural networks and nonlinear modelling for process engineering.
- Agakov, Felix
http://www.inf.ed.ac.uk/people/staff/Felix_Agakov.html - Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and causality.
- 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.
- Garcia, Christophe
http://www.csd.uoc.gr/~cgarcia - Computer vision, image analysis, neural networks.
- Versace, Massimiliano
http://www.maxversace.com - Neural networks applied to visual perception and computational modeling of mental disorders.
- Joshi, Prashant
http://www.igi.tugraz.at/joshi - Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.
- Pearlmutter, Barak
http://www-bcl.cs.may.ie/~barak/ - Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.
- Chu, Selina
http://www-scf.usc.edu/~selinach - Artificial intelligence, machine learning, data mining.
- Schein, Andrew I.
http://www.cis.upenn.edu/~ais - Machine learning approaches to data mining focussing on text mining applications.
- 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.
- Andonie, Razvan
http://www.cwu.edu/~andonie/ - Data structures for computational intelligence.
- Allan, Moray
http://www.morayallan.com/ - Computer vision, probabilistic models for image sequences, invariant features.
- Shkolnik, Alexander
http://web.mit.edu/shkolnik/www/ - Neurally controlled robotics.
- Wiegerinck, Wim
http://www.mbfys.ru.nl/mbfys/people/wimw/ - Inference in graphical models, mean field and variational approaches.
- Heskes, Tom
http://www.cs.ru.nl/~tomh/ - Learning and generalization in 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
- Olier, Ivan
http://www.lsi.upc.edu/~iaolier/ - Artificial intelligence, generative topographic map, missing data.
- Lerner, Uri N.
http://ai.stanford.edu/~uri/ - Hybrid and Bayesian networks.
- Koller, Daphne
http://ai.stanford.edu/~koller/ - Probabilistic models for complex uncertain domains.
- Dr Hooman Shadnia
http://ca.geocities.com/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.
- Saund, Eric
http://www2.parc.com/spl/members/saund/ - Intermediate level structure in vision.
- Cheung, Vincent
http://www.psi.toronto.edu/~vincent/ - Machine learning and probabilistic graphical models for computer vision and computational molecular biology.
- McCallum, Andrew
http://www.cs.umass.edu/~mccallum/ - Machine learning, text and information retrieval and extraction, reinforcement learning.
- Xing, Eric
http://www.cs.cmu.edu/~epxing/ - Statistical learning, machine learning approaches to computational biology, pattern recognition and control.
- Attias, Hagai
http://research.goldenmetallic.com/ - Graphical models, variational Bayes, independent factor analysis.
- Lawrence, Steve
http://labs.google.com/people/lawrence/ - Information dissemination and retrieval, machine learning and neural networks.
- Muresan, Raul C.
http://www.raulmuresan.home.ro/ - Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.
- Amari, Shun-ichi
http://www.brain.riken.jp/labs/mns/amari/home-E.html - Neural network learning, information geometry.
- 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.
- Dahlem, Markus A.
http://www.migraine-aura.org/EN/Markus_Dahlem.html - Neural network models of visual cortex to model neurological symptoms of migraine.
- Beal, Matthew J.
http://www.cse.buffalo.edu/faculty/mbeal - Bayesian inference, variational methods, graphical models, nonparametric Bayes.
- Rutkowski, Leszek
http://www.kik.pcz.czest.pl/~rutkowski/ - Neural networks, fuzzy systems, computational intelligence.
- Minka, Thomas P.
http://research.microsoft.com/~minka/ - Machine learning, computer vision, Bayesian methods.
- Lafferty, John D.
http://www.cs.cmu.edu/~lafferty/ - Statistical machine learning, text and natural language processing, information retrieval, information theory.
- 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.
- Paccanaro, Alberto
http://homes.gersteinlab.org/people/alberto/ - Learning distributed representation of concepts from relational data.
- Hansen, Lars Kai
http://eivind.imm.dtu.dk/staff/lkhansen/lkhansen.html - Neural network ensembles, adaptive systems and applications in neuroinformatics.
- de Garis, Hugo
http://www.iss.whu.edu.cn/degaris/ - Evolvable neural network models, neural networks for programmable hardware, large neural networks.
- Freeman, William T.
http://people.csail.mit.edu/billf/wtf.html - Bayesian perception, computer vision, image processing.
- Maass, Wolfgang
http://www.igi.tugraz.at/maass/ - Theory of computation, computation in spiking neurons.
- Brown, Andrew
http://www.ecs.soton.ac.uk/people/adb - Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
- 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.
- Olshausen, Bruno
http://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.
- Wunsch II, Donald C.
http://www.ece.umr.edu/acil/users/wunsch/biotest.html - Reinforcement Learning, Adaptive Critic Designs, Control, Optimization, Graph Theory, Bioinformatics, Intrusion Detection.
- Saul, Lawrence K.
http://www.cs.ucsd.edu/~saul/ - Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
- Prashant, Joshi
http://www.klab.caltech.edu/~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.
- 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.
- 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.
- Morris, Quaid
http://www.psi.utoronto.ca/~quaid/index.html - Machine learning for medical diagnosis and biological data analysis.
- Sallans, Brian
http://members.chello.at/hoebertz-sallans/sallans/index.html - Decision making under uncertainty, reinforcement learning, unsupervised learning.
- Zhou, Zhi-Hua
http://cs.nju.edu.cn/zhouzh/ - Neural computing, data mining, evolutionary computing, ensemble networks.
- Bach, Francis
http://www.di.ens.fr/~fbach/ - Machine learning, kernel methods, kernel independent component analysis and graphical models
- Malchiodi, Dario
http://homes.dsi.unimi.it/~malchiod/ - Machine learning, Learning from uncertain data.
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