Search Results for author: Ilja Bytschok

Found 6 papers, 0 papers with code

Spiking neurons with short-term synaptic plasticity form superior generative networks

no code implementations24 Sep 2017 Luziwei Leng, Roman Martel, Oliver Breitwieser, Ilja Bytschok, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici

In this work, we use networks of leaky integrate-and-fire neurons that are trained to perform both discriminative and generative tasks in their forward and backward information processing paths, respectively.

Stochastic inference with spiking neurons in the high-conductance state

no code implementations23 Oct 2016 Mihai A. Petrovici, Johannes Bill, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier

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 to the deterministic response of neurons measured in vitro.

Bayesian Inference Vocal Bursts Intensity Prediction

The high-conductance state enables neural sampling in networks of LIF neurons

no code implementations5 Jan 2016 Mihai A. Petrovici, Ilja Bytschok, Johannes Bill, Johannes Schemmel, Karlheinz Meier

The core idea of our approach is to separately consider two different "modes" of spiking dynamics: burst spiking and transient quiescence, in which the neuron does not spike for longer periods.

Bayesian Inference

Stochastic inference with deterministic spiking neurons

no code implementations13 Nov 2013 Mihai A. Petrovici, Johannes Bill, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier

The seemingly stochastic transient dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference.

Bayesian Inference

Stochasticity from function -- why the Bayesian brain may need no noise

no code implementations21 Sep 2018 Dominik Dold, Ilja Bytschok, Akos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici

An increasing body of evidence suggests that the trial-to-trial variability of spiking activity in the brain is not mere noise, but rather the reflection of a sampling-based encoding scheme for probabilistic computing.

Bayesian Inference

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