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bayes_for_stratos

bgnlm

Combining Variational Bayes and GMJMCMC for Scalable Inference on Bayesian Generalized Nonlinear Models, Philip Sebastian Hauglie Sommerfelt, 2023

deepbayes-2018

Seminars DeepBayes Summer School 2018

depmixs4pp

Adding adaptive simulated variable selection, and various prediction options for the standard depmixS4

effects-of-dietary-lipid-source-and-fish-size-on-steatosis-in-two-atlantic-salmon-populations

supplementary materials

emjmcmc2016

Bayesian model configuration, selection and averaging in complex regression contexts

islbbnn

Make Neural Networks more interpretable by using Input-Skip Latent Binary Bayesian Neural Networks (ISLBBNN). Allows for global explanation of predictions, and can also be used for local explanations.

r-worskhop

An intensive worksop for introduction to R

skweak

skweak: A software toolkit for weak supervision applied to NLP tasks

stin-300

selected lectures in spin 300

vadam

Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, Gal, and Srivastava

variational-inference-for-bayesian-neural-networks-under-model-and-parameter-uncertainty

Code base for producing the results reported in the paper Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty.

weak-supervision-for-ner

Framework to learn Named Entity Recognition models without labelled data using weak supervision.