Robert Legenstein | DeepAI

DeepAI AI Chat

Featured Co-authors

Feng Chen
73 publications
Johannes Schemmel
40 publications
Mihai A. Petrovici
22 publications
Sebastian Schmitt
22 publications
Wolfgang Maass
20 publications
Sebastian Otte
19 publications
Karlheinz Meier
19 publications
Zhaofei Yu
18 publications
Eric Müller
18 publications
Ozan Özdenizci
18 publications
Paul Müller
17 publications

∙ 07/29/2022

Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models

Image restoration under adverse weather conditions has been of significa...

6 Ozan Özdenizci, et al. ∙

∙ 05/23/2022

Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity

Memory is a key component of biological neural systems that enables the ...

0 Thomas Limbacher, et al. ∙

∙ 04/08/2021

Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks

In the paper, we show how scalable, low-cost trunk-like robotic arms can...

0 Manuel Traub, et al. ∙

∙ 06/19/2020

Oscillatory background activity implements a backbone for sampling-based computations in spiking neural networks

Various data suggest that the brain carries out probabilistic inference....

0 Michael G. Müller, et al. ∙

∙ 03/03/2020

Embodied Synaptic Plasticity with Online Reinforcement learning

The endeavor to understand the brain involves multiple collaborating res...

23 Jacques Kaiser, et al. ∙

∙ 03/20/2019

Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype

Advances in neuroscience uncover the mechanisms employed by the brain to...

8 Yexin Yan, et al. ∙

∙ 01/25/2019

Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets

The way how recurrently connected networks of spiking neurons in the bra...

0 Guillaume Bellec, et al. ∙

∙ 03/26/2018

Long short-term memory and Learning-to-learn in networks of spiking neurons

Networks of spiking neurons (SNNs) are frequently studied as models for ...

0 Guillaume Bellec, et al. ∙

∙ 11/14/2017

Deep Rewiring: Training very sparse deep networks

Neuromorphic hardware tends to pose limits on the connectivity of deep n...

0 Guillaume Bellec, et al. ∙

∙ 04/13/2017

Reward-based stochastic self-configuration of neural circuits

Synaptic connections between neurons in the brain are dynamic because of...

0 David Kappel, et al. ∙

∙ 03/17/2017

Pattern representation and recognition with accelerated analog neuromorphic systems

Despite being originally inspired by the central nervous system, artific...

0 Mihai A. Petrovici, et al. ∙

∙ 03/06/2017

Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System

Emulating spiking neural networks on analog neuromorphic hardware offers...

0 Sebastian Schmitt, et al. ∙

∙ 06/01/2016

CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling

Synaptic plasticity is implemented and controlled through over thousand ...

0 Zhaofei Yu, et al. ∙

∙ 04/20/2015

Network Plasticity as Bayesian Inference

General results from statistical learning theory suggest to understand n...

0 David Kappel, et al. ∙