People (124)
![Submit a Featured Link: [$19.00]](/images/AddF_Button.gif)
![Submit a Regular Link: [$9.00]](/images/AddR_Button.gif)
 Minsky, Marvin@ (12) |
- Top/Computers/Artificial Intelligence/People
- Top/Science/Social Sciences/Psychology/Cognitive/People
 Malchiodi, Dario   - Machine learning, Learning from uncertain data. - http://homes.dsi.unimi.it/~malchiod/    Bach, Francis - Machine learning, kernel methods, kernel independent component analysis and graphical models - http://www.di.ens.fr/~fbach/ Zhou, Zhi-Hua - Neural computing, data mining, evolutionary computing, ensemble networks. - http://cs.nju.edu.cn/zhouzh/ Sallans, Brian - Decision making under uncertainty, reinforcement learning, unsupervised learning. - http://members.chello.at/hoebertz-sallans/sallans/index.html Morris, Quaid - Machine learning for medical diagnosis and biological data analysis. - http://www.psi.utoronto.ca/~quaid/index.html Sejnowski, Terry - Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations. - http://www.salk.edu/faculty/faculty_details.php?id=48 Tipping, Mike - Varied machine learning and data analysis topics, including Bayesian inference, relevance vector machine, probabilistic principal component analysis and visualisation methods. - http://www.miketipping.com 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 biologic - http://www.klab.caltech.edu/~joshi/ Saul, Lawrence K. - Machine learning, pattern recognition, neural networks, voice processing, auditory computation. - http://www.cs.ucsd.edu/~saul/ Wunsch II, Donald C. - Reinforcement Learning, Adaptive Critic Designs, Control, Optimization, Graph Theory, Bioinformatics, Intrusion Detection. - http://www.ece.umr.edu/acil/users/wunsch/biotest.html Opper, Manfred - Statistical physics, information theory and applied probability and applications to machine learning and complex systems. - http://www.ncrg.aston.ac.uk/People/opperm/Welcome.html Olshausen, Bruno - Visual coding, statistics of images, independent components analysis. - http://redwood.berkeley.edu/bruno Saad, David - Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques. - http://www.ncrg.aston.ac.uk/People/saadd/Welcome.html Brown, Andrew - Machine learning of dynamic data, graphical models and Bayesian networks, neural networks. - http://www.ecs.soton.ac.uk/people/adb Maass, Wolfgang - Theory of computation, computation in spiking neurons. - http://www.igi.tugraz.at/maass/ Freeman, William T. - Bayesian perception, computer vision, image processing. - http://people.csail.mit.edu/billf/wtf.html de Garis, Hugo - Evolvable neural network models, neural networks for programmable hardware, large neural networks. - http://www.iss.whu.edu.cn/degaris/ Hansen, Lars Kai - Neural network ensembles, adaptive systems and applications in neuroinformatics. - http://eivind.imm.dtu.dk/staff/lkhansen/lkhansen.html Paccanaro, Alberto - Learning distributed representation of concepts from relational data. - http://homes.gersteinlab.org/people/alberto/ Brody, Carlos D. - Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology. - http://www.cshl.edu/public/SCIENCE/brody.html Lafferty, John D. - Statistical machine learning, text and natural language processing, information retrieval, information theory. - http://www.cs.cmu.edu/~lafferty/ Minka, Thomas P. - Machine learning, computer vision, Bayesian methods. - http://research.microsoft.com/~minka/ Rutkowski, Leszek - Neural networks, fuzzy systems, computational intelligence. - http://www.kik.pcz.czest.pl/~rutkowski/ Beal, Matthew J. - Bayesian inference, variational methods, graphical models, nonparametric Bayes. - http://www.cse.buffalo.edu/faculty/mbeal Dahlem, Markus A. - Neural network models of visual cortex to model neurological symptoms of migraine. - http://www.migraine-aura.org/EN/Markus_Dahlem.html De Wilde, Philippe - Brain inspired models of uncertainty, linguistic and fuzzy uncertainty, uncertainty in dynamic multi-user environments. - http://www.macs.hw.ac.uk/~pdw/ Amari, Shun-ichi - Neural network learning, information geometry. - http://www.brain.riken.jp/labs/mns/amari/home-E.html Muresan, Raul C. - Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures. - http://www.raulmuresan.home.ro/ Lawrence, Steve - Information dissemination and retrieval, machine learning and neural networks. - http://labs.google.com/people/lawrence/ Attias, Hagai - Graphical models, variational Bayes, independent factor analysis. - http://research.goldenmetallic.com/ Xing, Eric - Statistical learning, machine learning approaches to computational biology, pattern recognition and control. - http://www.cs.cmu.edu/~epxing/ McCallum, Andrew - Machine learning, text and information retrieval and extraction, reinforcement learning. - http://www.cs.umass.edu/~mccallum/ Cheung, Vincent - Machine learning and probabilistic graphical models for computer vision and computational molecular biology. - http://www.psi.toronto.edu/~vincent/ Koller, Daphne - Probabilistic models for complex uncertain domains. - http://ai.stanford.edu/~koller/ Olier, Ivan - Artificial intelligence, generative topographic map, missing data. - http://www.lsi.upc.edu/~iaolier/ De vito, Saverio - Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures - http://www.afs.enea.it/devito/ Wiegerinck, Wim - Inference in graphical models, mean field and variational approaches. - http://www.mbfys.ru.nl/mbfys/people/wimw/ Allan, Moray - Computer vision, probabilistic models for image sequences, invariant features. - http://www.morayallan.com/ 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 Schein, Andrew I. - Machine learning approaches to data mining focussing on text mining applications. - http://www.cis.upenn.edu/~ais Chu, Selina - Artificial intelligence, machine learning, data mining. - http://www-scf.usc.edu/~selinach Pearlmutter, Barak - Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging. - http://www-bcl.cs.may.ie/~barak/ Joshi, Prashant - Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons. - http://www.igi.tugraz.at/joshi Versace, Massimiliano - Neural networks applied to visual perception and computational modeling of mental disorders. - http://www.maxversace.com Garcia, Christophe - Computer vision, image analysis, neural networks. - http://www.csd.uoc.gr/~cgarcia Anthony, Martin - Computational learning theory, discrete mathematics. - http://www.maths.lse.ac.uk/Personal/martin/ Andrieu, Christophe - Particle filtering and Monte Carlo Markov Chain methods. - http://www.stats.bris.ac.uk/~maxca/ Agakov, Felix - Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and causality. - http://www.inf.ed.ac.uk/people/staff/Felix_Agakov.html Bulsari, A. - Neural networks and nonlinear modelling for process engineering. - http://www.abo.fi/~abulsari Wainwright, Martin - Statistical signal and image processing, natural image modelling, graphical models. - http://www.eecs.berkeley.edu/~martinw/ Murray-Smith, Roderick - Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces. - http://www.dcs.gla.ac.uk/~rod/ Russell, Stuart - Many aspects of probabilistic modelling, identity uncertainty, expressive probability models. - http://www.cs.berkeley.edu/~russell/ Dietterich, Thomas G. - Reinforcement learning, machine learning, supervised learning. - http://cs.oregonstate.edu/~tgd/ 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 Friedman, Nir - Learning of probabilistic models, applications to computational biology. - http://www.cs.huji.ac.il/~nir/ 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/ Williams, Christopher K. I. - Gaussian processes, image interpretation, graphical models, pattern recognition. - http://www.dai.ed.ac.uk/homes/ckiw/ MacKay, David - Bayesian theory and inference, error-correcting codes, machine learning. - http://www.inference.phy.cam.ac.uk/mackay/ 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/ Frey, Brendan J. - Iterative decoding, unsupervised learning, graphical models. - http://www.psi.utoronto.ca/~frey/ Cottrell, Garrison W. - An artrificial intelligence researcher who is an expert on neural networks. - http://charlotte.ucsd.edu/~gary/ Bishop, Chris - Graphical models, variational methods, pattern recognition. - http://research.microsoft.com/~cmbishop/ Roberts, Stephen - Machine learning and medical data analysis, independent component analysis and information theory. - http://www.robots.ox.ac.uk/~sjrob/ Herbrich, Ralph - Statistical learning theory, support vector machines and kernel methods. - http://www.research.microsoft.com/users/rherb/ 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/ Coolen, Ton - Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks. - http://www.mth.kcl.ac.uk/~tcoolen/ Roweis, Sam T. - Speech processing, auditory scene analysis, machine learning. - http://www.cs.toronto.edu/~roweis/ 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/ Kearns, Michael - Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems. - http://www.cis.upenn.edu/~mkearns/ LeCun, Yann - Handwritten recognition, convolutional networks, image compression. Noted for LeNet. - http://yann.lecun.com/ de Freitas, Nando - Bayesian inference, Markov chain Monte Carlo simulation, machine learning. - http://www.cs.ubc.ca/~nando/ 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/ Tishby, Naftali - Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science. - http://www.cs.huji.ac.il/~tishby/ Keysers, Daniel - Pattern recognition and statistical modelling for object recognition. - http://www-i6.informatik.rwth-aachen.de/~keysers/ Wallis, Guy - Object recognition, cognitive neuroscience, interaction between vision and motor movements. - http://www.uq.edu.au/~uqgwalli/ Welling, Max - Unsupervised learning, probabilistic density estimation, machine vision. - http://www.cs.utoronto.ca/~welling Kali, Szabolcs - Learning and memory in the brain, hippocampus. - http://www.gatsby.ucl.ac.uk/~szabolcs Kakade, Sham - Reinforcement learning and conditioning, mathematical models of neural processing. - http://www.gatsby.ucl.ac.uk/~sham Rasmussen, Carl Edward - Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models. - http://www.gatsby.ucl.ac.uk/~edward Wu, Yingnian - Stochastic generative models for complex visual phenomena. - http://www.stat.ucla.edu/~ywu/ Yedidia, Jonathan S. - Statistical methods for inference and learning. - http://www.merl.com/people/yedidia/ Wiskott, Laurenz - Face recognition, Invariances in learning and vision. - http://itb.biologie.hu-berlin.de/~wiskott/homepage.html Meila, Marina - Graphical models, learning in high dimensions, tree networks. - http://www.stat.washington.edu/mmp/ Boutilier, Craig - Decision making and planning under uncertainty, reinforcement learning, game theory and economic models. - http://www.cs.toronto.edu/~cebly/ Zemel, Richard - Unsupervised learning, machine learning, computational models of neural processing. - http://www.cs.utoronto.ca/~zemel/ Shuurmans, Dale - Computational learning, complex probability modelling. - http://www.lpaig.uwaterloo.ca/~dale/ Teh, Yee Whye - Learning and inference in complex probabilistic models. - http://www.cs.utoronto.ca/~ywteh Beveridge, Ross - Computer vision, model-based object recognition, face recognition. - http://www.cs.colostate.edu/~ross/ Honavar, Vasant - Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning. - http://www.cs.iastate.edu/~honavar/ Calvin, William H. - Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think. - http://faculty.washington.edu/wcalvin/ Bartlett, Marian Stewart - Image analysis with unsupervised learning, face recognition, facial expression analysis. - http://ergo.ucsd.edu/~marni/ Seung, Sebastian - Short-term memory, learning and memory in the brain, computational learning theory. - http://hebb.mit.edu/people/seung/ Sahani, Maneesh - Statistical analysis of neural data, experimental design in neuroscience. - http://www.gatsby.ucl.ac.uk/~maneesh/ Murphy, Kevin P. - Graphical models, machine learning, reinforcement learning. - http://www.cs.berkeley.edu/~murphyk Li, Zhaoping - Non-linear neural dynamics, visual segmentation, sensory processing. - http://www.gatsby.ucl.ac.uk/~zhaoping Oja, Erkki - Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis. - http://www.cis.hut.fi/oja/ Jaakkola, Tommi S. - Graphical models, variational methods, kernel methods. - http://www.ai.mit.edu/people/tommi Ghahramani, Zoubin - Sensorimotor control, unsupervised learning, probabilistic machine learning. - http://www.gatsby.ucl.ac.uk/~zoubin Ballard, Dana H. - Visual perception with neural networks. - http://www.cs.rochester.edu/users/faculty/dana Dayan , Peter - Representation and learning in neural processing systems, unsupervised learning, reinforcement learning. - http://www.gatsby.ucl.ac.uk/~dayan/ Adelson, Edward T. - Visual perception, machine vision, image processing. - http://www-bcs.mit.edu/people/adelson/ Neal, Radford - Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression. - http://www.cs.toronto.edu/~radford Jordan, Michael I. - Graphical models, variational methods, machine learning, reasoning under uncertainty. - http://www.cs.berkeley.edu/~jordan/ Becker, Sue - Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems. - http://www.science.mcmaster.ca/Psychology/sb.html |
|
