Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 11.4 — Using stochastic units to improve search [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 11.3 — Hopfield nets with hidden units [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 11.2 — Dealing with spurious minima [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 11.1 — Hopfield Nets [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 10.5 — Dropout [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 10.4 — Making full Bayesian learning practical [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 10.3 — The idea of full Bayesian learning [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 10.2 — Mixtures of Experts [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI 10.1 — Why it helps to combine models [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 9.6 — MacKay ‘s quick and dirty method [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 9.3 — Using noise as a regularizer [Neural Networks for Machine Learning]
Video AI Science, Geoffrey Hinton, Neural Network, University AI Lecture 15.2 — Deep autoencoders [Neural Networks for Machine Learning]
