Position paper: Bayesian deep learning in the age of large-scale ai
In the current landscape of deep learning research, there is a predominant emphasis on
achieving high predictive accuracy in supervised tasks involving large image and language …
achieving high predictive accuracy in supervised tasks involving large image and language …
Evolutionary variational inference for Bayesian generalized nonlinear models
PSH Sommerfelt, A Hubin - Neural Computing and Applications, 2024 - Springer
In the exploration of recently developed Bayesian Generalized Nonlinear Models (BGNLM),
this paper proposes a pragmatic scalable approximation for computing posterior …
this paper proposes a pragmatic scalable approximation for computing posterior …
Improving sparsity and interpretability of latent binary Bayesian neural networks by introducing input-skip connections
E Høyheim - 2024 - nmbu.brage.unit.no
Being able to model natural phenomena using mathematical equations has been a major
success story for researchers. Among various sophisticated methods, artificial neural …
success story for researchers. Among various sophisticated methods, artificial neural …
Outlier Detection in Bayesian Neural Networks: Exploring Pre-activations and Predictive Entropy
Describing uncertainty is one of the major issues in modern deep learning. Artificial
Intelligence models could be used with greater confidence by having solid methods for …
Intelligence models could be used with greater confidence by having solid methods for …
Combining Variational Bayes and GMJMCMC for Scalable Inference on Bayesian Generalized Nonlinear Models
PSH Sommerfelt - 2023 - duo.uio.no
We change the approach for computing posterior distributions in Bayesian Generalized
Nonlinear Models. We replace MCMC with variational Bayes, and approximate the posterior …
Nonlinear Models. We replace MCMC with variational Bayes, and approximate the posterior …
[PDF][PDF] Evolutionary variational inference for Bayesian generalized nonlinear models
PS Hauglie Sommerfelt, A Hubin - 2024 - nmbu.brage.unit.no
In the exploration of recently developed Bayesian Generalized Nonlinear Models (BGNLM),
this paper proposes a pragmatic scalable approximation for computing posterior …
this paper proposes a pragmatic scalable approximation for computing posterior …