94 citations · 390 across the 16 of their papers we have counts for
4 papers · 1 filter
Deterministic networks for probabilistic computing
Jakob Jordan, Mihai A. Petrovici, Oliver Breitwieser +4
Neural-network models of high-level brain functions such as memory recall and reasoning often rely on the presence of stochasticity. The majority of these models assumes that each…
Spiking neurons with short-term synaptic plasticity form superior generative networks
Luziwei Leng, Roman Martel, Oliver Breitwieser +5
Spiking networks that perform probabilistic inference have been proposed both as models of cortical computation and as candidates for solving problems in machine learning. However,…
Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware
Mihai A. Petrovici, Anna Schroeder, Oliver Breitwieser +3
How spiking networks are able to perform probabilistic inference is an intriguing question, not only for understanding information processing in the brain, but also for transferrin…
Pattern representation and recognition with accelerated analog neuromorphic systems
Mihai A. Petrovici, Sebastian Schmitt, Johann Klähn +33
Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit partic…