Efficient Learning Using Spiking Neural Networks Equipped With Affine Encoders and Decoders

Deep learning [6, 29] is a technology that has revolutionized many areas of modern life. The term describes the gradient-based training of deep neural networks. Since its breakthrough in image classification in 2012 [28], deep learning is essentially the only viable technology for this application. Moreover, it is the basis of multiple recent breakthroughs in science [25] and even mathematical research [14]. Recently, deep learning has received wide public attention through the advent of generative AI in the form of large language models such as ChatGPT [39]. It is well-documented that deep learning in modern applications can have extreme requirements on computational resources and the hardware requirements scale in an unsustainable way [52]. In constrained settings, this can become a serious bottleneck preventing the employment of deep learning methods. In addition, these comprehensive computations come with an immense environmental cost.