A neural network is a computational model inspired by the structure and function of the human brain. It consists of interconnected artificial neurons that process and transmit information, enabling machine learning tasks such as pattern recognition, classification, and regression by learning from labeled data.
Research demonstrates that overparametrization enhances quantum machine learning performance, surpassing classical computers. The study reveals the critical point at which adding parameters leads to improved network performance and easier training.
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