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02/17/2023
Theory of coupled neuronal-synaptic dynamics
In neural circuits, synapses influence neurons by shaping network dynami...
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07/25/2022
Dimension of Activity in Random Neural Networks
Neural networks are high-dimensional nonlinear dynamical systems that pr...
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02/05/2022
The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks
Understanding the asymptotic behavior of gradient-descent training of de...
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01/24/2022
Input correlations impede suppression of chaos and learning in balanced rate networks
Neural circuits exhibit complex activity patterns, both spontaneously an...
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06/08/2021
Credit Assignment Through Broadcasting a Global Error Vector
Backpropagation (BP) uses detailed, unit-specific feedback to train deep...
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04/14/2021
Neural population geometry: An approach for understanding biological and artificial neural networks
Advances in experimental neuroscience have transformed our ability to ex...
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12/29/2018
Training dynamically balanced excitatory-inhibitory networks
The construction of biologically plausible models of neural circuits is ...
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12/12/2018
Feedback alignment in deep convolutional networks
Ongoing studies have identified similarities between neural representati...
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10/09/2017
full-FORCE: A Target-Based Method for Training Recurrent Networks
Trained recurrent networks are powerful tools for modeling dynamic neura...
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05/03/2017
Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity
Neurons and networks in the cerebral cortex must operate reliably despit...
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08/22/2016
LFADS - Latent Factor Analysis via Dynamical Systems
Neuroscience is experiencing a data revolution in which many hundreds or...
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12/19/2014