Curriculum learning as a tool to uncover learning principles in the brain. - Daniel R. Kepple; Rainer Engelken; Kanaka Rajan (ICLR, 2022)

A time-resolved theory of information encoding in recurrent neural networks. - Rainer Engelken; Sven Goedeke (NeurIPS, 2022)

Input correlations impede suppression of chaos and learning in balanced rate networks. - Rainer Engelken; Alessandro Ingrosso; Ramin Khajeh; Sven Goedeke; L. F. Abbott (CoRR, 2022)

Input correlations impede suppression of chaos and learning in balanced firing-rate networks. - Rainer Engelken; Alessandro Ingrosso; Ramin Khajeh; Sven Goedeke; L. F. Abbott (PLoS Comput. Biol., 2022)

SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks. - Rainer Engelken (NeurIPS, 2023)

Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians. - Rainer Engelken (NeurIPS, 2023)

Sparse chaos in cortical circuits. - Rainer Engelken; Michael Monteforte; Fred Wolf 002 (CoRR, 2024)