Intuitively, PoRB-Nets work by trading off between the concentration and scale of the radial basis functions. Consider that a higher concentration of ba- sis functions allows for a smaller lengthscale but also a larger variance, since the basis functions add up.
PoRB-Nets: Poisson Process Radial Basis Function Networks ... Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1338- ...
Page 11. PoRB-Nets: Poisson Process Radial Basis Function Networks. (Appendix). Contents. A COVARIANCE DERIVATION. 3. A.1 CASE 1: HOMOGENEOUS POISSON PROCESS .
Citation: Coker B, Fernandez-Pradier M, Doshi-Velez F. PoRB-Nets: Poisson Process Radial Basis Function Networks. UAI. 2020 :1-59. Download ...
A novel prior over radial basis function networks (RBFNs) is presented that allows for independent specification of functional amplitude variance and ...
We introduce Poisson Process Radial Basis Function Networks (PoRB-Nets), an interpretable family of radial basis function networks (RBFNs) that employ a ...
Dec 12, 2019 · In this section, we introduce Poisson-process Radial. Basis function Networks (PoRB-NETs). ... (Consistency of PoRB-NETs) A radial basis ...
Duration: 8:02
Posted: Oct 14, 2020
Posted: Oct 14, 2020
People also ask
What is the radial basis function RBF model?
What is the RBF network architecture?
What is the difference between RBF and neural network?
What is the difference between MLP and RBF?
Papertalk is an open-source platform where scientists share video presentations about their newest scientific results - and watch, like + discuss them.
Dec 15, 2019 · Poisson Process Radial Basis Function Networks. (PoRB-NET) ck. ∼ N ... A PoRB-NET with uniform intensity function is Hellinger consistent as.