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- School of Science
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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Artificial Intelligence
- Instructor(s)
- Suzumura Toyotaro Machida Motoya
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Intensive ()
- Group
- -
- Course number
- ART.T454
- Credits
- 2
- Academic year
- 2021
- Offered quarter
- 1-2Q
- Syllabus updated
- 2021/5/17
- Lecture notes updated
- 2021/5/17
- Language used
- English
- Access Index
-
Lecture
Lecture 1 Advanced topics on graph algorithms (Suzumura)
2021.6.16(Wed.) 9-10Session
Lecture
Lecture 2 Advanced topics on graph database (Suzumura)
2021.6.23(Wed.) 9-10Session
Lecture
Lecture 3 Advanced topics on graph learning (Suzumura)
2021.6.30(Wed.) 9-10Session
Lecture
Lecture 4 Motivation for Monte Carlo simulation / Rejection algorithm (Machida)
2021.7.6(Tue.) 1-2Session
Lecture
Lecture 5 Advanced topics on graph neural network (I) (Suzumura)
2021.7.7(Wed.) 9-10Session
Lecture
Lecture 6 Markov chain Monte Carlo method / Metropolis algorithm (Machida)
2021.7.9(Fri.) 1-2Session
Lecture
Lecture 7 Discrete structure and Gibbs sampler / Gibbs algorithm (Machida)
2021.7.13(Tue.) 1-2Session
Lecture
Lecture 8 Advanced topics on graph neural network (II) (Suzumura)
2021.7.14(Wed.) 9-10Session
Lecture
Lecture 9 How long should you run it? / Perfect sampling algorithms (Machida)
2021.7.16(Fri.) 1-2Session
Lecture
Lecture 10 Hidden Markov model and dynamic decision making / Viterbi algorithm (Machida)
2021.7.20(Tue.) 1-2Session
Lecture
Lecture 11 Advanced topics on high performance computing and graph learning for massive graphs (Suzumura)
2021.7.21(Wed.) 9-10Session
Lecture
Lecture 12 Quantum computation and sampling / Shor’s algorithm (Machida)
2021.7.27(Tue.) 1-2Session
Lecture
Lecture 13 Advanced topics on graph learning and use cases (Suzumura)
2021.7.28(Wed.) 9-10Session
Lecture
Lecture 14 Brownian motion and intertwining dual / Pitman-type algorithm (Machida)
2021.7.30(Fri.) 1-2Session
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