Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
The study points up interpretability as a critical barrier to trust and adoption. Many AI-based cybersecurity tools function ...
Abstract: In this article, we present a highly accurate recurrent neural network (RNN) for behavioral modeling and digital predistortion (DPD) of radio frequency (RF) power amplifiers (PAs). We ...
1 Cognitive Computational Neuroscience Group, Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany 2 Neuroscience Lab, University Hospital Erlangen, ...
Recurrent neural networks (RNNs) have been foundational in machine learning for addressing various sequence-based problems, including time series forecasting and natural language processing. RNNs are ...
This important study provides a new perspective on why preparatory activity occurs before the onset of movement. The authors report that when there is a cost on the inputs, the optimal inputs should ...
The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...
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