research
∙
05/24/2023
Block-local learning with probabilistic latent representations
The ubiquitous backpropagation algorithm requires sequential updates acr...
share
research
∙
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...
research
∙
03/03/2020
Embodied Synaptic Plasticity with Online Reinforcement learning
The endeavor to understand the brain involves multiple collaborating res...
research
∙
12/27/2019
Structural plasticity on an accelerated analog neuromorphic hardware system
In computational neuroscience, as well as in machine learning, neuromorp...
research
∙
11/14/2019
Attention on Abstract Visual Reasoning
Attention mechanisms have been boosting the performance of deep learning...
research
∙
03/20/2019
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype
Advances in neuroscience uncover the mechanisms employed by the brain to...
research
∙
11/14/2017
Deep Rewiring: Training very sparse deep networks
Neuromorphic hardware tends to pose limits on the connectivity of deep n...
research
∙
04/13/2017
Reward-based stochastic self-configuration of neural circuits
Synaptic connections between neurons in the brain are dynamic because of...
research
∙
06/01/2016
CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling
Synaptic plasticity is implemented and controlled through over thousand ...
research
∙
04/20/2015