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Starts 24 June 2025 00:26
Ends 24 June 2025
Networks that Adapt to Intrinsic Dimensionality Beyond the Domain
Inside Livermore Lab
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Overview
Explore neural networks' ability to adapt to intrinsic dimensionality, focusing on ReLU networks approximating functions with dimensionality-reducing feature maps. Gain insights into manifold learning and data analysis.
Syllabus
- Introduction to Neural Networks and Intrinsic Dimensionality
- ReLU Networks and Function Approximation
- Feature Maps and Dimensionality Reduction
- Manifold Learning
- Adaptive Network Architectures
- Advanced Topics in Manifold Learning
- Practicals and Hands-on Sessions
- Conclusion and Future Directions
Subjects
Data Science