Researchers explore quantum neural networks via mixture of experts

Researchers have established a mean-field limit for Mixture of Experts (MoE) models trained using gradient flow in supervised learning scenarios. Their findings demonstrate that as the number of experts increases, the model's parameters converge towards a probability measure that satisfies a nonlinear continuity equation. This convergence rate is explicitly dependent on the number of experts, and the study applies these results to MoE models generated by quantum neural networks. AI

影响 Theoretical advancement in understanding MoE convergence, potentially impacting future model architectures.

排序理由 Academic paper detailing theoretical advancements in machine learning models.

在 arXiv cs.LG 阅读 →

• Anderson Melchor Hernandez
• arXiv
• Mixture of Experts
• quantum neural networks

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