research
∙
06/12/2023
On the Dynamics of Learning Time-Aware Behavior with Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have shown great success in modeling ti...
share
research
∙
12/11/2022
Energy-based General Sequential Episodic Memory Networks at the Adiabatic Limit
The General Associative Memory Model (GAMM) has a constant state-dependa...
research
∙
04/04/2022
Forward Signal Propagation Learning
We propose a new learning algorithm for propagating a learning signal an...
research
∙
04/01/2021
Replay in Deep Learning: Current Approaches and Missing Biological Elements
Replay is the reactivation of one or more neural patterns, which are sim...
research
∙
09/05/2019
Minibatch Processing in Spiking Neural Networks
Spiking neural networks (SNNs) are a promising candidate for biologicall...
research
∙
04/12/2019
Locally Connected Spiking Neural Networks for Unsupervised Feature Learning
In recent years, Spiking Neural Networks (SNNs) have demonstrated great ...
research
∙
08/24/2018
STDP Learning of Image Patches with Convolutional Spiking Neural Networks
Spiking neural networks are motivated from principles of neural systems ...
research
∙
08/09/2018
Error Forward-Propagation: Reusing Feedforward Connections to Propagate Errors in Deep Learning
We introduce Error Forward-Propagation, a biologically plausible mechani...
research
∙
07/24/2018
Unsupervised Learning with Self-Organizing Spiking Neural Networks
We present a system comprising a hybridization of self-organized map (SO...
research
∙
06/04/2018
