Filippo Moro, Pau Aceituno, Laura Kriener, Melika Payvand The Role of Temporal Hierarchy in Spiking Neural Networks, ArXiv, 2024

Göltz, Julian and Weber, Jimmy and Kriener, Laura and Billaudelle, Sebastian and Lake, Peter and Schemmel, Johannes and Payvand, Melika and A. Petrovici, Mihai DelGrad: Exact event-based gradients in spiking networks for training
delays and weights, ArXiv, 2024

Kriener, Laura and Göltz, Julian and Petrovici, Mihai A. The Yin-Yang dataset, Neuro-Inspired Computational Elements Conference 107-111, 2022

Göltz, J. and Kriener, L. and Baumbach, A. and Billaudelle, S. and Breitwieser, O. and Cramer, B. and Dold, D. and Kungl, A. F. and Senn, W. and Schemmel, J. and Meier, K. and Petrovici, M. A. Fast and energy-efficient neuromorphic deep learning with first-spike times, Nature Machine Intelligence 823-835, 2021

Paul Haider, Benjamin Ellenberger, Laura Kriener, Jakob Jordan, Walter Senn, Mihai A. Petrovici Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons, Neurips, 2021