AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Electroencephalography (EEG) foundation models (FMs) promise transferable neural representations, yet their advantages over strong supervised baselines and their prospects for further scaling remain unclear. To address these questions, we introduce EEG-Arena, an open-source benchmark covering 30 EEG FMs and 25 supervis...
Neural Architecture Search (NAS) offers a promising pathway to automate the design of deep neural networks, yet it faces a significant challenge in balancing computational efficiency with search effectiveness in a huge search space. Coarse-to-fine (C2F) NAS methods mitigate this by narrowing the architecture search to...
The proposed parallel multi-compartment spiking neuron (PMSN) presents a promising solution to harness the computational advantages of detailed biological neurons, enabling high-performance and efficient temporal processing on neuromorphic computing systems.
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