4 citations · 13 across the 20 of their papers we have counts for
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A biologically plausible neural network for local supervision in cortical microcircuits
Siavash Golkar, David Lipshutz, Yanis Bahroun +2
The backpropagation algorithm is an invaluable tool for training artificial neural networks; however, because of a weight sharing requirement, it does not provide a plausible model…
A simple normative network approximates local non-Hebbian learning in the cortex
Siavash Golkar, David Lipshutz, Yanis Bahroun +2
To guide behavior, the brain extracts relevant features from high-dimensional data streamed by sensory organs. Neuroscience experiments demonstrate that the processing of sensory i…
A biologically plausible neural network for Slow Feature Analysis
David Lipshutz, Charlie Windolf, Siavash Golkar +1
Learning latent features from time series data is an important problem in both machine learning and brain function. One approach, called Slow Feature Analysis (SFA), leverages the…
Biologically plausible single-layer networks for nonnegative independent component analysis
David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii
An important problem in neuroscience is to understand how brains extract relevant signals from mixtures of unknown sources, i.e., perform blind source separation. To model how the…
A biologically plausible neural network for multi-channel Canonical Correlation Analysis
David Lipshutz, Yanis Bahroun, Siavash Golkar +2
Cortical pyramidal neurons receive inputs from multiple distinct neural populations and integrate these inputs in separate dendritic compartments. We explore the possibility that c…
Customer-server population dynamics in heavy traffic
Rami Atar, Prasenjit Karmakar, David Lipshutz
We study a many-server queueing model with server vacations, where the population size dynamics of servers and customers are coupled: a server may leave for vacation only when no c…