The best kind of follow-up article isn’t one that clarifies a topic that someone got wrong (although I do love that, ...
Artificial intelligence (AI) and computational modeling are transforming the landscape of neuroscience, offering unprecedented opportunities to detect, ...
New applications of AI and machine learning techniques were presented at Neuroscience 2025, the annual meeting of the Society for Neuroscience and the world’s largest source of emerging news about ...
Abstract: We consider the use of polar codes in edge computing and communications applications, and to achieve energy efficiency, we propose implementation of neural network-based decoders for them ...
Clevert, D.-A., Untertiner, T., and Hochreiter, S. (2016). Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). arXiv [Preprint]. Available ...
Engineers at Duke University have constructed a group of AI bots that together can solve complex design problems nearly as well as a fully trained scientist. The results, the researchers say, show how ...
Code associated with the paper "Gan He, Tiejun Huang and Kai Du, (2025). Going deeper with morphologically detailed neural networks by error-backpropagating mirror neuron" (soon on biorxiv when ready) ...
Abstract: We propose the self-denoising network (SDNet), a self-supervised network based on a convolutional neural network (CNN), for Brillouin trace denoising. With the target noisy image as the only ...
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