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

    https://cbl.eng.cam.ac.uk/publications/kao-cur-op-neurobiol-2019.pdf
    7 Jun 2024: This challenge is especiallyrelevant given the recent shi in focus from static analysesto dynamical descriptions of circuit computations [4, 10, 17,26••, 20, 24]. ... 964–976. [24] E. D. Remington et al. “Flexible sensorimotor compu-tations
  3. CMR7

    https://cbl.eng.cam.ac.uk/publications/hennequin-nips-2014.pdf
    7 Jun 2024: The fact that these networks are fastersamplers is in line with recent machine learning studies on how non-reversible Markov chains canmix faster than their reversible counterparts [24]. ... 24] Akihisa Ichiki and Masayuki Ohzeki. Violation of detailed
  4. Non-reversible Gaussian processes for identifyinglatent dynamical…

    https://cbl.eng.cam.ac.uk/publications/rutten-neurips-2020.pdf
    7 Jun 2024: neural population dynamics. Network: Computation in Neural Systems, 23:24–47. Buesing, L., Macke, J. ... Tr(AA′. >). = δ′ (24)f(τ)f′(τ) dτ = δ′. (25). We will refer to Eq.
  5. Chapter 3A Theoretical Framework for the Dynamicsof Multiple…

    https://cbl.eng.cam.ac.uk/publications/remme-book-chapter-2012.pdf
    7 Jun 2024: J Neurosci, 18(19):7613–24. Medvedev, G. S., Wilson, C. J., Callaway, J.
  6. Exact natural gradient in deep linear networks andapplication to ...

    https://cbl.eng.cam.ac.uk/publications/bernacchia-nips-2018.pdf
    7 Jun 2024: In a deeplinear network, xL is equal to. xL = Wx (24)where W is the total weight matrix product across layers, given by.
  7. PHYSICAL REVIEW E 86, 011909 (2012) Non-normal amplification in ...

    https://cbl.eng.cam.ac.uk/publications/hennequin-pre-2012.pdf
    7 Jun 2024: The graph topology is known to affect dynamicalproperties such as correlations and network synchronization[24] or performance in attractor tasks [25].
  8. Manifold GPLVMs for discovering non-Euclideanlatent structure in…

    https://cbl.eng.cam.ac.uk/publications/jensen-neurips-2020.pdf
    7 Jun 2024: pSn. (g) =.  2πn12Γ(n12 ). 1 (23)pT. n. (g) = [2π]n (24).
  9. The stabilized supralinear network accounts for the contrast…

    https://cbl.eng.cam.ac.uk/publications/holt-biorxiv-2023.pdf
    7 Jun 2024: In the linearized approximation, the LFP power-spectrum(see Eqs. (24)–(26) in Methods) can be expressed in termsof the so-called Jacobian matrix, i.e.
  10. Neuron Article Optimal Control of Transient Dynamicsin Balanced…

    https://cbl.eng.cam.ac.uk/publications/hennequin-neuron-2014.pdf
    7 Jun 2024: correlated (r 0.24) than pairs of excitation and inhibition cur-rents taken from different neurons (r 0.12; compare red andblack in Figures 8E and 8F).
  11. ILQR-VAE : CONTROL-BASED LEARNING OF INPUT-DRIVEN DYNAMICS WITH…

    https://cbl.eng.cam.ac.uk/publications/schimel-iclr-2022.pdf
    7 Jun 2024: Network: Computation in Neural Systems, 23:24–47. Champion, K., Lusch, B., Kutz, J.

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