日本語

Course Code etc
Academic Year 2024
College Graduate School of Artificial Intelligence and Science
Course Code VR481
Theme・Subtitle
Class Format Online (all classes are online)
Class Format (Supplementary Items) 発話を伴う授業を発話を伴う授業を学内で受講する場合は1204教室の利用可
Campus Lecture
Campus Ikebukuro
Semester Spring Semester
DayPeriod・Room Wed.6・
Credit 2
Course Number AIR6400
Language Japanese
Class Registration Method Course Code Registration
Grade (Year) Required 配当年次は開講学部のR Guideに掲載している科目表で確認してください。
prerequisite regulations
Acceptance of Other Colleges 履修登録システムの『他学部・他研究科履修不許可科目一覧』で確認してください。
course cancellation -(履修中止制度なし/ No system for cancellation)
Online Classes Subject to 60-Credit Upper Limit
Relationship with Degree Policy 各授業科目は、学部・研究科の定める学位授与方針(DP)や教育課程編成の方針(CP)に基づき、カリキュラム上に配置されています。詳細はカリキュラム・マップで確認することができます。
Notes
Text Code VR481

【Course Objectives】

The aim of this course is to learn advanced topics in statistical modeling using Bayesian approaches, including MCMC, variational inferences, and related topics.

【Course Contents】

This course explains the methods for posterior inference in Bayesian modeling.
Topics to be covered in the first half of this course include the elementary expositions of MCMC, the implementation of MCMC in Python, and practical coding for posterior inference via MCMC.
Topics to be covered in the second half of this course include the fundamentals of variational inference, its application in natural language processing (ex. LDA), and the variational auto-encoder.

※Please refer to Japanese Page for details including evaluations, textbooks and others.