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