VS298: Slides
From RedwoodCenter
Jump to navigationJump to search
Many lectures from Oct 7th on are available in video form thanks to Jeff Teeters. Please check here.
- Sep 02 - Introduction
- Sep 18 - Supervised learning
- Sep 23/25 - Unsupervised learning
- Sep 30/Oct 2 - Sparse coding
- Oct 7 - Sparse coding applications
- Oct 14 - Self-organizing maps
- Oct 16 - Manifold models
- Oct 21/23 - Attractor neural networks
- Oct 28 - Recurrent neural networks and dynamical systems (David Zipser)
- Oct 30 - Bayesian probability theory and generative models
- Nov 4 - Mixture of Gaussians model and Boltzmann machines
- Nov 18 - Sparse coding and ICA
- Nov 20 - Kalman filter
- Nov 25 - Spiking neuron models
- Dec 9 - Encoding meaning with high-dimensional random vectors
