Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Dabiran, Nastaran"'
Autor:
Dabiran, Nastaran, Robinson, Brandon, Sandhu, Rimple, Khalil, Mohammad, Poirel, Dominique, Sarkar, Abhijit
Neural networks (NNs) are primarily developed within the frequentist statistical framework. Nevertheless, frequentist NNs lack the capability to provide uncertainties in the predictions, and hence their robustness can not be adequately assessed. Conv
Externí odkaz:
http://arxiv.org/abs/2310.15614
Autor:
Dabiran, Nastaran, Robinson, Brandon, Sandhu, Rimple, Khalil, Mohammad, Pettit, Chris L., Poirel, Dominique, Sarkar, Abhijit
Sparse Bayesian learning (SBL) has been extensively utilized in data-driven modeling to combat the issue of overfitting. While SBL excels in linear-in-parameter models, its direct applicability is limited in models where observations possess nonlinea
Externí odkaz:
http://arxiv.org/abs/2310.14749