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Cambridge University Reporter Special
https://www.reporter.admin.cam.ac.uk/reporter/2005-06/weekly/6023/9.html28 Jan 2022: Information Engineering at Cambridge spans the broad areas of control, communications, signal, speech, image and vision processing, machine learning, and computational neuroscience. ... the cellular basis of learning and memory, control of neuronal -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2022-23 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2022-23describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2021-22 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2021-22describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2020-21 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2020-21describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2018-19 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2018-19describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2019-20 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2019-20describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2017-18 …
https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2017-18describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in -
Function factorization using warped Gaussian processes Mikkel N.…
https://mlg.eng.cam.ac.uk/pub/pdf/Sch09.pdf13 Feb 2023: 2. Relation to other methods. Function factorization with warped Gaussian processpriors (FF-WGP) generalizes a number of other wellknown machine learning techniques including matrixand tensor factorization, linear regression, and warpedGaussian -
Notices by Faculty Boards, etc. - Cambridge University Reporter 6310
https://www.reporter.admin.cam.ac.uk/reporter/2012-13/weekly/6310/section6.shtml30 May 2013: p. 4F12. Computer vision and robotics. IIBM2. p. 4F13. Machine learning. ... c. 4G3. Computational neuroscience. c. IIBL5. 4A13. Combustion and IC engines. -
1 Set Unit Title Mode IIBM1 4A2 Computational Fluid ...
https://teaching21-22.eng.cam.ac.uk/download/file/5782IIBL4 4G3 Computational Neuroscience cIIBL2 4G4 Biomimetics cIIBM6 4G5 Materials and Molecules: Modelling, Simulation and Machine Learning cIIBM1 4G6 Cellular and Molecular Biomechanics pIIBL11 4G9 Biomedical Engineering c. ... 4A7 Aircraft Aerodynamics
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