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Srdjan Ostojic

2 accepted papers

2022

Extracting computational mechanisms from neural data using low-rank RNNs

NeurIPS 2022accept

An influential framework within systems neuroscience posits that neural computations can be understood in terms of low-dimensional dynamics in recurrent circuits. A number of methods have thus been developed to extract latent dynamical systems from neural recordings, but inferring models that are bo…

Cited by 43SourcePDFScholar
2020

The interplay between randomness and structure during learning in RNNs

NeurIPS 2020oral

Training recurrent neural networks (RNNs) on low-dimensional tasks has been widely used to model functional biological networks. However, the solutions found by learning and the effect of initial connectivity are not well understood. Here, we examine RNNs trained using gradient descent on different…