论文标题
通过峰值依赖性重量推断克服重量传输问题
Overcoming the Weight Transport Problem via Spike-Timing-Dependent Weight Inference
论文作者
论文摘要
我们提出了解决重量传输问题的解决方案,该解决方案质疑了返回算法的生物学合理性。我们基于对泄漏整合和开火神经元的(近似)动力学的理论分析得出我们的方法。我们表明,单独使用尖峰时序胜过现有的生物学上合理的方法,用于峰值神经网络模型中的突触重量推断。此外,我们提出的方法更灵活,适用于任何尖峰神经元模型,在实施需要多少参数方面是保守的,并且可以通过最小的计算开销部署进行在线部署。这些特征及其生物学合理性使其成为单个突触中重量推断的有吸引力的机制。
We propose a solution to the weight transport problem, which questions the biological plausibility of the backpropagation algorithm. We derive our method based upon a theoretical analysis of the (approximate) dynamics of leaky integrate-and-fire neurons. We show that the use of spike timing alone outcompetes existing biologically plausible methods for synaptic weight inference in spiking neural network models. Furthermore, our proposed method is more flexible, being applicable to any spiking neuron model, is conservative in how many parameters are required for implementation and can be deployed in an online-fashion with minimal computational overhead. These features, together with its biological plausibility, make it an attractive mechanism underlying weight inference at single synapses.