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1 - 5 of 5 search results for `neuroscience of learning`

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  2. AI speeds up drug design for Parkinson’s ten-fold | University of…

    https://www.cam.ac.uk/research/news/ai-speeds-up-drug-design-for-parkinsons-ten-fold
    Thumbnail for AI speeds up drug design for Parkinson’s ten-fold | University of Cambridge 17 Apr 2024: Machine learning is having a real impact on drug discovery – it’s speeding up the whole process of identifying the most promising candidates. ... Reference:. Robert I Horne et al. ‘Discovery of Potent Inhibitors of α-Synuclein Aggregation Using
    By: @cambridge_uni

  3. CMR7

    https://cbl.eng.cam.ac.uk/publications/hennequin-nips-2014.pdf
    4 Jul 2024: laurence@gatsby.ucl.ac.uk. Máté Lengyel1. m.lengyel@eng.cam.ac.uk. 1Computational & Biological Learning Lab, Dept. of Engineering, University of Cambridge, UK2Gatsby Computational Neuroscience Unit, University College London, UK. ... Máté Lengyel1

  4. ILQR-VAE : CONTROL-BASED LEARNING OF INPUT-DRIVEN DYNAMICS WITH…

    https://cbl.eng.cam.ac.uk/publications/schimel-iclr-2022.pdf
    4 Jul 2024: While iLQR-VAE could find applications in many fields as a general approach to learning stochasticnonlinear dynamical systems, here we focus on neuroscience case studies. ... DeepLabCut: markerless pose estimation of user-defined body parts with deep

  5. Neuroscience out of control:control-theoretic perspectives on neural…

    https://cbl.eng.cam.ac.uk/publications/kao-cur-op-neurobiol-2019.pdf
    4 Jul 2024: More generally, dissecting the circuit basis of com-plex computations such as motor control or reinforcementlearning will benefit from a deeper integration of control the-ory, machine learning, and neuroscience. ... Cunningham. “Towards the neu-ral

  6. Manifold GPLVMs for discovering non-Euclideanlatent structure in…

    https://cbl.eng.cam.ac.uk/publications/jensen-neurips-2020.pdf
    4 Jul 2024: Neural computation, 25:626–649. Titsias, M. K. (2009). Variational learning of inducing variables in sparse Gaussian processes. ... To highlight the importance of unsupervised non-Euclidean learning methods in neuroscience and toillustrate the

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