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CSC413/2516 Winter 2021 Tutorial 9 - Information Theory March 11th, 2021 Presented by Jonathan Lorraine Original notes by Silviu Pitis Source: https://csc413-2020.github.io/assets/tutorials/tut09_infotheory.pdf

CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"

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Page 1: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"

CSC413/2516 Winter 2021Tutorial 9 - Information Theory

March 11th, 2021Presented by Jonathan Lorraine

Original notes by Silviu PitisSource:

https://csc413-2020.github.io/assets/tutorials/tut09_infotheory.pdf

https://csc413-2020.github.io/assets/tutorials/tut09_infotheory.pdf
Page 2: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 3: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 4: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 5: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 6: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 7: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 8: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 9: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 10: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 11: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 12: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 13: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 14: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 15: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 16: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 17: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 18: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 19: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 20: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 21: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 22: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 23: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 24: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 25: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 26: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 27: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 28: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 29: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 30: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 31: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 32: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 33: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 34: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 35: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 36: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 37: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 38: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 39: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 40: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 41: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 42: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"
Page 43: CSC413/2516 Winter 2021 Tutorial 9 - Information Theory ...uses Jensen's inequality. The final line is the variational or evidence lower bound (ELBO) on log p(x). While this "1.S.-Jensen"

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