71 citations · 137 across the 5 of their papers we have counts for
5 papers
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…
Stochastic inference with spiking neurons in the high-conductance state
Mihai A. Petrovici, Johannes Bill, Ilja Bytschok +2
The highly variable dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference but stand in apparent contrast…
The high-conductance state enables neural sampling in networks of LIF neurons
Mihai A. Petrovici, Ilja Bytschok, Johannes Bill +2
The apparent stochasticity of in-vivo neural circuits has long been hypothesized to represent a signature of ongoing stochastic inference in the brain. More recently, a theoretical…
Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons
Dimitri Probst, Mihai A. Petrovici, Ilja Bytschok +4
The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Ba…
Stochastic inference with deterministic spiking neurons
Mihai A. Petrovici, Johannes Bill, Ilja Bytschok +2
The seemingly stochastic transient dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference. In vitro neuro…