| 1 |
A brief review of linear algebra and orthogonal decomposition techniques |
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| 2 |
A brief review of linear algebra and orthogonal decomposition techniques |
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| 3 |
A brief review of linear algebra and orthogonal decomposition techniques |
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| 4 |
Modeling of data, Ridge regression, Automatic selection |
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| 5 |
Modeling of data, Ridge regression, Automatic selection |
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| 6 |
Inverse Theory |
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| 7 |
Numerical methods for solving partial differential equations |
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| 8 |
Numerical methods for solving partial differential equations |
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| 9 |
Numerical methods for solving partial differential equations |
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| 10 |
Numerical methods for solving partial differential equations |
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| 11 |
Introduction to Optimization |
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| 12 |
Classical Methods of Unconstrained Optimization |
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| 13 |
Classical Methods of Unconstrained Optimization |
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| 14 |
Classical Methods of Unconstrained Optimization |
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| 15 |
Classical Methods of Unconstrained Optimization |
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| 16 |
GA as an example of Global Optimization |
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| 17 |
Ant colony optimization |
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| 18 |
An Introduction to Artificial Neural Networks |
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| 19 |
MLP & RBF neural networks |
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| 20 |
Special topics in neural networks |
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| 21 |
Special topics in neural networks |
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| 22 |
Molecular simulation |
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