Latent variables enabled effective energy-based neural networks. The key problem with the Little/Hopfield neural network was its limited memory capacity. This problem was resolved when Hinton, Ackley, and Sejnowski introduced the notion of latent variables, creating the Boltzmann machine. Seven key papers define the evolution of energy-based neural networks. Previously, we examined the first two… Continue reading Latent Variables Enabled Effective Energy-Based Neural Networks: Seven Key Papers (Part 2 of 3)
Seven Key Papers for Energy-Based Neural Networks and Deep Learning (Part 1 of 3)
Seven key papers provide us with the evolutionary timeline for energy-based neural networks, up through and including deep learning. The timeline for these papers begins with William Little’s 1974 work on the first energy-based neural network, and then John Hopfield’s 1982 expansion on Little’s concepts, up through deep learning architectures as described by Hinton and… Continue reading Seven Key Papers for Energy-Based Neural Networks and Deep Learning (Part 1 of 3)