A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware. - Eric Müller 001; Elias Arnold; Oliver Breitwieser; Milena Czierlinski; Arne Emmel; Jakob Kaiser; Christian Mauch; Sebastian Schmitt; Philipp Spilger; Raphael Stock; Yannik Stradmann; Johannes Weis; et al. (CoRR, 2022)

Spiking Neural Network Equalization for IM/DD Optical Communication. - Elias Arnold; Georg Böcherer; Eric Müller 001; Philipp Spilger; Johannes Schemmel; Stefano Calabrò; Maxim Kuschnerov (CoRR, 2022)

hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2. - Philipp Spilger; Elias Arnold; Luca Blessing; Christian Mauch; Christian Pehle; Eric Müller 001; Johannes Schemmel (NICE, 2023)

Spiking Neural Network Linear Equalization: Experimental Demonstration of 2km 100Gb/s IM/DD PAM4 Optical Transmission. - Georg Böcherer; Florian Strasser; Elias Arnold; Youxi Lin; Johannes Schemmel; Stefano Calabrò; Maxim Kuschnerov (OFC, 2023)

Event-based Backpropagation for Analog Neuromorphic Hardware. - Christian Pehle; Luca Blessing; Elias Arnold; Eric Müller 001; Johannes Schemmel (CoRR, 2023)

jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware. - Eric Müller 001; Moritz Althaus; Elias Arnold; Philipp Spilger; Christian Pehle; Johannes Schemmel (NICE, 2024)

Towards Large-scale Network Emulation on Analog Neuromorphic Hardware. - Elias Arnold; Philipp Spilger; Jan V. Straub; Eric Müller 001; Dominik Dold; Gabriele Meoni; Johannes Schemmel (CoRR, 2024)

Live Demonstration: Event-based Learning in Spiking Networks on Analog Hardware using JAX. - Elias Arnold; Eric Müller 001; Johannes Schemmel (ISCAS, 2025)

Short-reach Optical Communications: A Real-world Task for Neuromorphic Hardware. - Elias Arnold; Eike-Manuel Edelmann; Alexander von Bank; Eric Müller 001; Laurent Schmalen; Johannes Schemmel (NICE, 2025)