STATS 271
Probabilistic Models of Visual Cortex
Statistics · 4 units · Graduate courses (200-299)
Recommended: Computer Science 180. Introduction to state-of-art computational models of mammalian visual cortex, with topics in low-, mid-, and high-level vision. Discussion of relevant evidence from anatomy, electrophysiology, imaging (e.g., fMRI), and psychophysics. Concentration on mathematical modeling of these phenomena, taking into account recent progress in probabilistic models of computer vision and developments in machine learning.
S/U or letter grading.
Requisites
Official UCLA wording
Requisite: course 100B or Mathematics 33A.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
STATS 271
- STATS 100BIntroduction to Mathematical Statistics
- STATS 100AIntroduction to Probability
- MATH 32BCalculus of Several Variables
- MATH 170AProbability Theory I
2 direct requisites. Showing 17 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
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