2019 Advanced Topics in Artificial Intelligence S

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Academic unit or major
Graduate major in Artificial Intelligence
Instructor(s)
Machida Motoya  Alexander Shibakov 
Course component(s)
Lecture
Day/Period(Room No.)
Intensive ()  
Group
-
Course number
ART.T454
Credits
2
Academic year
2019
Offered quarter
1-2Q
Syllabus updated
2019/6/13
Lecture notes updated
2019/6/20
Language used
English
Access Index
Supplementary documents 

Lecture

Lecture 1 Preliminary discussion for mathematics of qunatum computation, and class organization.

2019.5.22(Wed.) 5-6Session

Lecture

Lecture 2 Physics and mathematics of simple (single qubit) systems.

2019.5.22(Wed.) 7-8Session

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Lecture 3 Quantum state spaces: tensor products and n qubit systems

2019.5.22(Wed.) 9-9Session

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Lecture 4 Quantum state spaces: tensor products and n qubit systems

2019.5.29(Wed.) 5-5Session

Lecture

Lecture 5 Quantum probability, entanglement, and Bell's theorem

2019.5.29(Wed.) 6-7Session

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Lecture 6 Quantum state transformations and quantum gates

2019.5.29(Wed.) 8-9Session

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Lecture 7 Introduction to quantum computation

2019.6.5(Wed.) 5-6Session

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Lecture 8 Simple quantum algorithms: Deutsch-Jozsa, and Simon's problems

2019.6.5(Wed.) 7-8Session

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Lecture 9 Shor’s algorithm and quantum state observations

2019.6.5(Wed.) 9-9Session

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Lecture 10 Shor’s algorithm and quantum state observations

2019.6.12(Wed.) 5-5Session

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Lecture 11 Introduction to Monte Carlo simulation

2019.6.12(Wed.) 6-7Session

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Lecture 12 Markov chain Monte Carlo (MCMC) algorithms

2019.6.12(Wed.) 8-9Session

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Lecture 13 Introduction to Brownian motion

2019.6.19(Wed.) 5-6Session

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Lecture 14 Introduction to stochastic differential equations (SDE)

2019.6.19(Wed.) 7-8Session

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Lecture 15 Pitman theorem, Kent characteristic diffusions, and an application of SDE to Monte Carlo simulations

2019.6.19(Wed.) 9-9Session

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Lecture 16 Pitman theorem, Kent characteristic diffusions, and an application of SDE to Monte Carlo simulations

2019.6.26(Wed.) 5-5Session

Lecture

Lecture 17 When do we stop running a diffusion process and declare a sample from a stationary distribution?

2019.6.26(Wed.) 6-7Session

Lecture

Lecture 18 Can Monte Carlo methodology allow us to implement Shor’s algorithm?

2019.6.26(Wed.) 8-9Session

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