research
∙
04/20/2023
Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout
Spiking neural networks (SNNs) have gained attention as models of sparse...
share
research
∙
07/23/2022
A Taxonomy of Recurrent Learning Rules
Backpropagation through time (BPTT) is the de facto standard for trainin...
research
∙
11/24/2021
Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications
In the context of solving inverse problems for physics applications with...
research
∙
11/05/2018
A Biologically Plausible Learning Rule for Deep Learning in the Brain
Researchers have proposed that deep learning, which is providing importa...
research
∙
06/13/2018
An image representation based convolutional network for DNA classification
The folding structure of the DNA molecule combined with helper molecules...
research
∙
10/13/2017
Efficient Computation in Adaptive Artificial Spiking Neural Networks
Artificial Neural Networks (ANNs) are bio-inspired models of neural comp...
research
∙
03/14/2017
Conditional Time Series Forecasting with Convolutional Neural Networks
We present a method for conditional time series forecasting based on the...
research
∙
03/11/2016