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Starts 7 June 2025 22:33
Ends 7 June 2025
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An Overview of Entropy-Regularized Optimal Transport and Schrödinger Bridges
Delve into entropy-regularized optimal transport theory and Schrödinger bridges, exploring applications in statistics, data science, and generative AI, with insights from physics, stochastic processes, and PDEs.
Centre for Networked Intelligence, IISc
via YouTube
Centre for Networked Intelligence, IISc
2544 Courses
58 minutes
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Overview
Delve into entropy-regularized optimal transport theory and Schrödinger bridges, exploring applications in statistics, data science, and generative AI, with insights from physics, stochastic processes, and PDEs.
Syllabus
- Introduction to Optimal Transport
- Entropy-Regularized Optimal Transport
- Schrödinger Bridges
- Applications in Generative AI
- Connections to Physics and PDEs
- Advanced Topics and Current Research
- Practical Implementation
- Conclusion and Further Reading
Origins and Basic Concepts
Applications in Statistics and Data Science
Definition and Mathematical Formulation
Sinkhorn Distances and Algorithms
Computational Advantages
Historical Context and Physical Interpretation
Stochastic Processes and Connection to Optimal Transport
Formulation via Entropy Minimization
Machine Learning and Data Synthesis
Generative Models Using Optimal Transport
Kinetic Theory and Transport Equations
Role of PDEs in Describing Dynamics
Recent Advances in Entropy Regularization
Open Problems and Future Directions
Software and Tools for Computation
Case Studies and Examples
Summary of Key Concepts
Suggested Books and Papers for Further Study
Subjects
Data Science
