David Kappel | DeepAI

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Featured Co-authors

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∙ 05/24/2023

Block-local learning with probabilistic latent representations

The ubiquitous backpropagation algorithm requires sequential updates acr...

0 David Kappel, et al. ∙

∙ 06/13/2022

EGRU: Event-based GRU for activity-sparse inference and learning

The scalability of recurrent neural networks (RNNs) is hindered by the s...

17 Anand Subramoney, 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. ∙

∙ 12/27/2019

Structural plasticity on an accelerated analog neuromorphic hardware system

In computational neuroscience, as well as in machine learning, neuromorp...

16 Sebastian Billaudelle, et al. ∙

∙ 11/14/2019

Attention on Abstract Visual Reasoning

Attention mechanisms have been boosting the performance of deep learning...

13 Lukas Hahne, 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. ∙

∙ 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. ∙

∙ 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. ∙

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