Nicolai Haug

Exponential Map Models as an Interpretable Framework for Generating Neural Spatial Representations

This paper introduces an exponential map framework to generate interpretable neural spatial representations, showing how algebraic conditions enable path and translational invariance and biologically relevant spatial tuning.

Metamodelling of a two-population spiking neural network

The paper applies metamodels to a spiking neural network to approximate its dynamics and invert parameter distributions from simulation outputs.