Cengiz Pehlevan

Efficiency and robustness partition the solution space for memory in recurrent networks

In computational neuroscience, task-trained recurrent neural networks (RNNs) are commonly used as a testbed for exploring the space of recurrent circuit solutions compatible with a particular function. However, these networks are subject to inductive biases that may be misaligned with those of biological circuits, whic...