48 citations · 69 across the 6 of their papers we have counts for
6 papers
Transient dynamics of associative memory models
David G. Clark
Associative memory models such as the Hopfield network and its dense generalizations with higher-order interactions exhibit a "blackout catastrophe" -- a discontinuous transition w…
Theory of coupled neuronal-synaptic dynamics
David G. Clark, L. F. Abbott
In neural circuits, synaptic strengths influence neuronal activity by shaping network dynamics, and neuronal activity influences synaptic strengths through activity-dependent plast…
Dimension of activity in random neural networks
David G. Clark, L. F. Abbott, Ashok Litwin-Kumar
Neural networks are high-dimensional nonlinear dynamical systems that process information through the coordinated activity of many connected units. Understanding how biological and…
Credit Assignment Through Broadcasting a Global Error Vector
David G. Clark, L. F. Abbott, SueYeon Chung
Backpropagation (BP) uses detailed, unit-specific feedback to train deep neural networks (DNNs) with remarkable success. That biological neural circuits appear to perform credit as…
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis
David G. Clark, Jesse A. Livezey, Kristofer E. Bouchard
Linear dimensionality reduction methods are commonly used to extract low-dimensional structure from high-dimensional data. However, popular methods disregard temporal structure, re…
Spiking Linear Dynamical Systems on Neuromorphic Hardware for Low-Power Brain-Machine Interfaces
David G. Clark, Jesse A. Livezey, Edward F. Chang +1
Neuromorphic architectures achieve low-power operation by using many simple spiking neurons in lieu of traditional hardware. Here, we develop methods for precise linear computation…