Taught by: Mehrdad Jazayeri and Josh Tenenbaum, MIT (June 9, 2015)
Video: Bayesian Methods: Brain and Cognitive Perspectives (1:13:59)
Description: An introduction to Bayesian estimation and its application to estimating visual contrast from neural activity.
Slides:
- Bayesian Tutorial (PDF) - Lecture slides by Mehrdad Jazayeri
- Bayesian tutorial (KEY) - Lecture slides by Mehrdad Jazayeri
Additional Resources:
- Exercises
- Tom Griffiths’ reading list on Bayesian methods
- Mathematicalmonk’s videos on Machine Learning: Recommended by Josh Tenenbaum as “probably the single best way I can think of for someone to teach themselves machine learning and relevant topics in stats, from both Bayesian and non-Bayesian perspectives”
- Griffiths, T. L., Kemp, C. & Tenenbaum, J. B. (2008) Bayesian Models of Cognition, in Ron Sun (ed.), The Cambridge Handbook of Computational Cognitive Modeling. Cambridge University Press.
- Kording, K. (2007) “Decision Theory: What ‘Should’ the Nervous System Do?” Science 318(5850): 606–610.
- Ghahramani, Z. (2015) “Probabilistic Machine Learning and Artificial Intelligence,” Nature 521: 452–459.
- Murphy, K. P. (2007) “Conjugate Bayesian Analysis of the Gaussian Distribution (PDF)”
- Roweis, S. (1999) “Gaussian Identities (PDF)”
- “Conjugate prior” Wikipedia page
