Zobrazeno 1 - 10
of 5 204
pro vyhledávání: '"A. van Gerven"'
Publikováno v:
HemaSphere, Vol 7, Iss S1, Pp 45-46 (2023)
Externí odkaz:
https://doaj.org/article/ae5380e2491b4fbab9b8283aea0599e9
Implementing AI algorithms on event-based embedded devices enables real-time processing of data, minimizes latency, and enhances power efficiency in edge computing. This research explores the deployment of a spiking recurrent neural network (SRNN) wi
Externí odkaz:
http://arxiv.org/abs/2408.12978
The stability of complex networks, from power grids to biological systems, is crucial for their proper functioning. It is thus important to control such systems to maintain or restore their stability. Traditional approaches rely on real-time state me
Externí odkaz:
http://arxiv.org/abs/2408.08263
Artificial intelligence techniques are increasingly being applied to solve control problems, but often rely on black-box methods without transparent output generation. To improve the interpretability and transparency in control systems, models can be
Externí odkaz:
http://arxiv.org/abs/2406.02765
A significant increase in the commercial use of deep neural network models increases the need for efficient AI. Node pruning is the art of removing computational units such as neurons, filters, attention heads, or even entire layers while keeping net
Externí odkaz:
http://arxiv.org/abs/2405.17506
Recurrent neural networks (RNNs) hold immense potential for computations due to their Turing completeness and sequential processing capabilities, yet existing methods for their training encounter efficiency challenges. Backpropagation through time (B
Externí odkaz:
http://arxiv.org/abs/2405.08967
The backpropagation algorithm remains the dominant and most successful method for training deep neural networks (DNNs). At the same time, training DNNs at scale comes at a significant computational cost and therefore a high carbon footprint. Convergi
Externí odkaz:
http://arxiv.org/abs/2405.02385
Epilepsy is one of the most common neurological disorders globally, affecting millions of individuals. Despite significant advancements, the precise mechanisms underlying this condition remain largely unknown, making accurately predicting and prevent
Externí odkaz:
http://arxiv.org/abs/2404.03409
Autor:
ElGazzar, Ahmed, van Gerven, Marcel
The unprecedented availability of large-scale datasets in neuroscience has spurred the exploration of artificial deep neural networks (DNNs) both as empirical tools and as models of natural neural systems. Their appeal lies in their ability to approx
Externí odkaz:
http://arxiv.org/abs/2403.14510
Backpropagation (BP) remains the dominant and most successful method for training parameters of deep neural network models. However, BP relies on two computationally distinct phases, does not provide a satisfactory explanation of biological learning,
Externí odkaz:
http://arxiv.org/abs/2310.00965