Neural networks have emerged as a powerful framework for addressing complex problems across numerous scientific domains. In particular, the interplay between neural network models and constraint ...
Mark R. Anderson of Strategic News Service, the Future in Review Conferences and Pattern Computer. Popular methods of artificial intelligence have an “explainability problem” — the inability to see ...
2hon MSN
Dopamine under control: Precision regulation of inhibition shapes learning, memory and mental health
For decades, dopamine has been celebrated in neuroscience as the quintessential "reward molecule"—a chemical herald of ...
Recent advances at the intersection of neural networks and inverse scattering problems have transformed traditional approaches to imaging and material characterisation. Inverse scattering involves ...
Generative artificial intelligence (AI) — such as ChatGPT and Dalle-2 — is undoubtedly one of the most groundbreaking and discussed technologies in recent history. Its applications and related issues ...
Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
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