Publications

David G. Clark, Haim Sompolinsky (2024). Simplified derivations for high-dimensional convex learning problems. arXiv.

arXiv

David G. Clark, Owen Marschall, Alexander van Meegen, Ashok Litwin-Kumar (2024). Connectivity structure and dynamics of nonlinear recurrent neural networks. arXiv.

arXiv

David G. Clark, L.F. Abbott (2024). Theory of coupled neuronal-synaptic dynamics. Physical Review X.

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David G. Clark, Manuel Beiran (2024). Structure of activity in multiregion recurrent neural networks. arXiv.

arXiv

David G. Clark, L.F. Abbott, Ashok Litwin-Kumar (2023). Dimension of activity in random neural networks. Physical Review Letters.

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Walter Fischler-Ruiz, David G. Clark, Narendra Joshi, Virginia Devi-Chou, Lacey Kitch, Mark Schnitzer, L.F. Abbott, Richard Axel (2021). Olfactory landmarks and path integration converge to form a cognitive spatial map. Neuron.

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David G. Clark, L.F. Abbott, SueYeon Chung (2021). Credit assignment through broadcasting a global error vector. NeurIPS 2021.

arXiv Code

David G. Clark, Jesse Livezey, Kristofer Bouchard (2019). Unsupervised discovery of temporal structure in noisy data with dynamical components analysis. NeurIPS 2019.

arXiv Code

Rebecca Carney, Kristofer Bouchard, Paolo Calafiura, David G. Clark, David Donofrio, Maurice Garcia-Sciveres, Jesse Livezey (2017). Neuromorphic Kalman filter implementation in IBM's TrueNorth. Journal of Physics: Conference Series.

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