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Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2023-24 …
https://teaching.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2023-24describe 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 -
Computational Learning and Memory Group
https://cbl.eng.cam.ac.uk/lengyel/people/9 Jul 2024: He did his PhD in computational neuroscience and machine learning at UCL, under the supervision of Neil Burgess and Maneesh Sahani. ... His main interests lie in neuroscience, machine learning, and their intersection. -
Research Assistants | Cambridge Centre for Neuropsychiatric Research
https://ccnr.ceb.cam.ac.uk/Team/Research-Assistants17 Jul 2024: During my studies there, I developed strong skills in applied data science and machine learning, as well as fundamental knowledge of neural computation and computational cognitive neuroscience, focused on realistic simulation ... health. Contact: -
Computational and Biological Learning Laboratory | Department of…
https://www.eng.cam.ac.uk/research/academic-divisions/information-engineering/research-groups/computational-and-biologicalComputational and Biological Learning Laboratory. The Computational and Biological Learning Laboratory uses engineering approaches to understand the brain and to develop artificial learning systems. ... Research includes Bayesian learning, computational -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2021-22 …
https://teaching.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://teaching.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, 2022-23 …
https://teaching.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, 2017-18 …
https://teaching.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 -
Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2019-20 …
https://teaching.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, 2018-19 …
https://teaching.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
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