167 citations · 257 across the 7 of their papers we have counts for
3 papers · 1 filter
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan +3
Recently, deep feedforward neural networks have achieved considerable success in modeling biological sensory processing, in terms of reproducing the input-output map of sensory neu…
Universality and individuality in neural dynamics across large populations of recurrent networks
Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub +2
Task-based modeling with recurrent neural networks (RNNs) has emerged as a popular way to infer the computational function of different brain regions. These models are quantitative…
Deep Learning Models of the Retinal Response to Natural Scenes
Lane T. McIntosh, Niru Maheswaranathan, Aran Nayebi +2
A central challenge in neuroscience is to understand neural computations and circuit mechanisms that underlie the encoding of ethologically relevant, natural stimuli. In multilayer…