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  2. Neuroscience out of control Control-theoretic methods for…

    https://cbl.eng.cam.ac.uk/news/hennequin_cosyne_2019.pdf
    25 Jun 2024: new method, regularised, stable). Â = argmaxA logp(y0:T |A). System identification. ... the effect of stimulation. Outlook. control-theoretic perspectives on RNNs offers new ways of.
  3. Neuroscience out of control:control-theoretic perspectives on neural…

    https://cbl.eng.cam.ac.uk/publications/kao-cur-op-neurobiol-2019.pdf
    25 Jun 2024: In particular, monkeys struggle to learn new mappingsthat require M1 to produce activity outside its intrinsic man-ifold [19, 55]. ... D. Miller. “Balanced amplifi-cation: a new mechanism of selective amplificationof neural activity paerns”.
  4. Exact natural gradient in deep linear networks andapplication to ...

    https://cbl.eng.cam.ac.uk/publications/bernacchia-nips-2018.pdf
    25 Jun 2024: Representations. Bishop, C. M. (2016). Pattern recognition and machine learning. Springer-Verlag New York. ... 2014). New insights and perspectives on the natural gradient method. arXiv preprintarXiv:1412.1193.
  5. CMR7

    https://cbl.eng.cam.ac.uk/publications/hennequin-nips-2014.pdf
    25 Jun 2024: However, time becomes a fundamental bottleneckin such sampling-based probabilistic representations: the quality of inferences de-pends on how fast the neural circuit generates new, uncorrelated samples fromits stationary distribution (the
  6. Chapter 3A Theoretical Framework for the Dynamicsof Multiple…

    https://cbl.eng.cam.ac.uk/publications/remme-book-chapter-2012.pdf
    25 Jun 2024: Chapter 3A Theoretical Framework for the Dynamicsof Multiple Intrinsic Oscillators in SingleNeurons. Michiel W.H. Remme, Máté Lengyel, and Boris S. Gutkin. Abstract The dendritic tree contributes significantly to the elementarycomputations a
  7. Non-reversible Gaussian processes for identifyinglatent dynamical…

    https://cbl.eng.cam.ac.uk/publications/rutten-neurips-2020.pdf
    25 Jun 2024: We introduced a measure of second-order non-reversibility and derived a new family ofGPs for which any sample has lower probability of occurring in reverse. ... This is a new result that we derived which we were not ableto find in the existing literature.
  8. Manifold GPLVMs for discovering non-Euclideanlatent structure in…

    https://cbl.eng.cam.ac.uk/publications/jensen-neurips-2020.pdf
    25 Jun 2024: Here,we propose a new probabilistic latent variable model to simultaneously identifythe latent state and the way each neuron contributes to its representation in anunsupervised way. ... This is achieved by combining a Bayesian GPLVM with recently
  9. PHYSICAL REVIEW E 86, 011909 (2012) Non-normal amplification in ...

    https://cbl.eng.cam.ac.uk/publications/hennequin-pre-2012.pdf
    25 Jun 2024: 1(a)]. Furthermore, the “purelynon-normal” part of the amplification of the external noisyinput in the original network of neurons corresponds to theactivity fluctuations in the new feedforward network whereall
  10. ILQR-VAE : CONTROL-BASED LEARNING OF INPUT-DRIVEN DYNAMICS WITH…

    https://cbl.eng.cam.ac.uk/publications/schimel-iclr-2022.pdf
    25 Jun 2024: However, identifying complex dynamical systems is a hard nonlin-ear filtering and learning problem that calls for new computational techniques (Kutschireiter et al.,2020). ... N. (2018). Superior arm-movementdecoding from cortex with a new,
  11. Neuron Article Optimal Control of Transient Dynamicsin Balanced…

    https://cbl.eng.cam.ac.uk/publications/hennequin-neuron-2014.pdf
    25 Jun 2024: Neuron. Article. Optimal Control of Transient Dynamicsin Balanced Networks Supports Generationof Complex MovementsGuillaume Hennequin,1,2, Tim P. Vogels,1,3,4 and Wulfram Gerstner1,41School of Computer and Communication Sciences and Brain Mind
  12. The stabilized supralinear network accounts for the contrast…

    https://cbl.eng.cam.ac.uk/publications/holt-biorxiv-2023.pdf
    25 Jun 2024: The stabilized supralinear network accounts for the contrast dependenceof visual cortical gamma oscillations. Caleb J. Holt1a, Kenneth D. Miller2 and Yashar Ahmadian3. 1aInstitute of Neuroscience, Department of Physics, University of Oregon, OR,

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