NEVESIM: event-driven neural simulation framework with a Python interface. - Dejan Pecevski; David Kappel; Zeno Jonke (Frontiers Neuroinformatics, 2014)

STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning. - David Kappel; Bernhard Nessler; Wolfgang Maass 001 (PLoS Comput. Biol., 2014)

Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring. - David Kappel; Stefan Habenschuss; Robert Legenstein; Wolfgang Maass 001 (NIPS, 2015)

Network Plasticity as Bayesian Inference. - David Kappel; Stefan Habenschuss; Robert Legenstein; Wolfgang Maass 001 (PLoS Comput. Biol., 2015)

Hamiltonian synaptic sampling in a model for reward-gated network plasticity. - Zhaofei Yu; David Kappel; Robert Legenstein; Sen Song; Feng Chen 007; Wolfgang Maass 001 (CoRR, 2016)

Reward-based stochastic self-configuration of neural circuits. - David Kappel; Robert Legenstein; Stefan Habenschuss; Michael Hsieh; Wolfgang Maass 001 (CoRR, 2017)

Deep Rewiring: Training very sparse deep networks. - Guillaume Bellec; David Kappel; Wolfgang Maass 001; Robert Legenstein (ICLR (Poster), 2018)

Attention on Abstract Visual Reasoning. - Lukas Hahne; Timo Lüddecke; Florentin Wörgötter; David Kappel (CoRR, 2019)

Embodied Synaptic Plasticity With Online Reinforcement Learning. - Jacques Kaiser; Michael Hoff 001; Andreas Konle; Juan Camilo Vasquez Tieck; David Kappel; Daniel Reichard; Anand Subramoney; Robert Legenstein; Arne Roennau; Wolfgang Maass 001; Rüdiger Dillmann (Frontiers Neurorobotics, 2019)

Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype. - Yexin Yan; David Kappel; Felix Neumärker; Johannes Partzsch; Bernhard Vogginger; Sebastian Höppner; Steve B. Furber; Wolfgang Maass 001; Robert Legenstein; Christian Mayr 001 (IEEE Trans. Biomed. Circuits Syst., 2019)

Event-based Neural Network for ECG Classification with Delta Encoding and Early Stopping. - Matthias Jobst; Chen Liu 031; Johannes Partzsch; Yexin Yan; David Kappel; Hector A. Gonzalez; Yue Ji; Bernhard Vogginger; Christian Mayr 001 (EBCCSP, 2020)

Adaptive Extreme Edge Computing for Wearable Devices. - Erika Covi; Elisa Donati; Hadi Heidari; David Kappel; Xiangpeng Liang; Melika Payvand; Wei Wang 209 (CoRR, 2020)

Structural plasticity on an accelerated analog neuromorphic hardware system. - Sebastian Billaudelle; Benjamin Cramer; Mihai A. Petrovici; Korbinian Schreiber; David Kappel; Johannes Schemmel; Karlheinz Meier (Neural Networks, 2021)

Decision Making by a Neuromorphic Network of Volatile Resistive Switching Memories. - Saverio Ricci; David Kappel; Christian Tetzlaff; Daniele Ielmini; Erika Covi (ICECS 2022, 2022)

EGRU: Event-based GRU for activity-sparse inference and learning. - Anand Subramoney; Khaleelulla Khan Nazeer; Mark Schöne; Christian Mayr 001; David Kappel (CoRR, 2022)

Efficient recurrent architectures through activity sparsity and sparse back-propagation through time. - Anand Subramoney; Khaleelulla Khan Nazeer; Mark Schöne; Christian Mayr 001; David Kappel (ICLR, 2023)

Block-local learning with probabilistic latent representations. - David Kappel; Khaleelulla Khan Nazeer; Cabrel Teguemne Fokam; Christian Mayr 001; Anand Subramoney (CoRR, 2023)

Language Modeling on a SpiNNaker 2 Neuromorphic Chip. - Khaleelulla Khan Nazeer; Mark Schöne; Rishav Mukherji; Christian Mayr 001; David Kappel; Anand Subramoney (CoRR, 2023)

CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning. - Nicolas Diekmann; Sandhiya Vijayabaskaran; Xiangshuai Zeng; David Kappel; Matheus Chaves Menezes; Sen Cheng (Frontiers Neuroinformatics, 2023)

Tunable synaptic working memory with volatile memristive devices. - Saverio Ricci; David Kappel; Christian Tetzlaff; Daniele Ielmini; Erika Covi (Neuromorph. Comput. Eng., 2023)

Language Modeling on a SpiNNaker2 Neuromorphic Chip. - Khaleelulla Khan Nazeer; Mark Schöne; Rishav Mukherji; Bernhard Vogginger; Christian Mayr 001; David Kappel; Anand Subramoney (AICAS, 2024)

Weight Sparsity Complements Activity Sparsity in Neuromorphic Language Models. - Rishav Mukherji; Mark Schöne; Khaleelulla Khan Nazeer; Christian Mayr 001; David Kappel; Anand Subramoney (ICONS, 2024)

Scalable Event-by-Event Processing of Neuromorphic Sensory Signals with Deep State-Space Models. - Mark Schöne; Neeraj Mohan Sushma; Jingyue Zhuge; Christian Mayr 001; Anand Subramoney; David Kappel (ICONS, 2024)

Coincidence Detection with an Analog Spiking Neuron Exploiting Ferroelectric Polarization. - Paolo Gibertini; Luca Fehlings; Thomas Mikolajick; Elisabetta Chicca; David Kappel; Erika Covi (ISCAS, 2024)

Neuromorphic hardware for sustainable AI data centers. - Bernhard Vogginger; Amirhossein Rostami; Vaibhav Jain; Sirine Arfa; Andreas Hantsch; David Kappel; Michael Schäfer; Ulrike Faltings; Hector A. Gonzalez; Chen Liu 031; Christian Mayr 001 (CoRR, 2024)

Asynchronous Stochastic Gradient Descent with Decoupled Backpropagation and Layer-Wise Updates. - Cabrel Teguemne Fokam; Khaleelulla Khan Nazeer; Lukas König; David Kappel; Anand Subramoney (CoRR, 2024)

State-space models can learn in-context by gradient descent. - Neeraj Mohan Sushma; Yudou Tian; Harshvardhan Mestha; Nicolò Colombo; David Kappel; Anand Subramoney (CoRR, 2024)

STREAM: A Universal State-Space Model for Sparse Geometric Data. - Mark Schöne; Yash Bhisikar; Karan Bania; Khaleelulla Khan Nazeer; Christian Mayr 001; Anand Subramoney; David Kappel (CoRR, 2024)

Inverting Visual Representations with Detection Transformers. - Jan Rathjens; Shirin Reyhanian; David Kappel; Laurenz Wiskott (CoRR, 2024)

Global remapping emerges as the mechanism for renewal of context-dependent behavior in a reinforcement learning model. - David Kappel; Sen Cheng (Frontiers Comput. Neurosci., 2024)

Synapses learn to utilize stochastic pre-synaptic release for the prediction of postsynaptic dynamics. - David Kappel; Christian Tetzlaff (PLoS Comput. Biol., 2024)