Mathematical Aspects of Deep Learning
GPTKB entity
Statements (32)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic
|
| gptkbp:appliesTo |
gptkb:artificial_intelligence
gptkb:machine_learning computer vision natural language processing |
| gptkbp:focusesOn |
neural networks
optimization generalization expressivity |
| gptkbp:hasResearchCenter |
robustness
explainability adversarial examples theoretical analysis of neural networks training dynamics |
| https://www.w3.org/2000/01/rdf-schema#label |
Mathematical Aspects of Deep Learning
|
| gptkbp:relatedTo |
gptkb:mathematics
deep learning |
| gptkbp:studies |
gptkb:complexity_theory
gptkb:information_theory learning theory stochastic processes function approximation gradient descent random matrix theory convergence regularization representation learning capacity loss landscapes overparameterization |
| gptkbp:bfsParent |
gptkb:Gitta_Kutyniok
|
| gptkbp:bfsLayer |
6
|