发现物理学习方法中参数守恒规律，提升训练可靠性
A Conservation Law for Equilibrium Propagation and Coupled Learning
- 在连续时间小扰动下，参数守恒量保持不变
- 该守恒律使线性电路训练收敛更可靠
- 对物理启发式学习模型有重要实践意义
本文证明，在连续时间、小扰动极限下，物理学习方法中的耦合学习（CL）与平衡传播（EP）会保持可训练参数的类质量守恒量。该守恒律在多种物理相关设置中均成立。进一步表明，此守恒律约束了训练动态，使线性电路在关键场景下的收敛性更加可靠。最后讨论了该守恒律的实际影响。
原文摘要 · Abstract (English)
In this paper we show that the physical learning methods known as coupled learning (CL) and equilibrium propagation (EP) conserve a mass-like quantity in the trainable parameters in the continuous-time, small-nudging limit. We prove that this conservation holds in a broad range of physically relevant settings. We then show that the conservation law constrains the training dynamics in a way that makes convergence reliable in important settings for linear circuits. We conclude by discussing some practical implications of this conservation law.
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