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DeepOnet Decomposition
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Classroom Contents
Deep Learning and Computations of PDEs by Siddhartha Mishra
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- 1 Intro
- 2 Partial Differential Equations (PDES)
- 3 Uncertainty Quantification
- 4 Supervised learning with Deep Neural networks
- 5 Supervised learning for high-d Parametric PDES
- 6 Refined Error Estimates
- 7 Training on Low-Discrepancy Sequences
- 8 PDE constrained Optimization
- 9 Tsunami in the Mediterranean sea
- 10 DL for Many-Query Problems: Further Issues
- 11 Operator Learning
- 12 DeepOnet Decomposition
- 13 Bounds on Reconstruction Error
- 14 Bounds on Encoding Error
- 15 Bounds on the Approximation Error
- 16 Out of Distribution Evaluations
- 17 Deep learning and High-dimensional PDES
