Pinned Repositories
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.
portfolio
Personal webpage
R-worskhop
An intensive worksop for introduction to R
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.
aliaksah's Repositories
aliaksah/EMJMCMC2016
Bayesian model configuration, selection and averaging in complex regression contexts
aliaksah/depmixS4pp
Adding adaptive simulated variable selection, and various prediction options for the standard depmixS4
aliaksah/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.
aliaksah/Bayes_for_STRATOS
aliaksah/BGNLM
Combining Variational Bayes and GMJMCMC for Scalable Inference on Bayesian Generalized Nonlinear Models, Philip Sebastian Hauglie Sommerfelt, 2023
aliaksah/deepbayes-2018
Seminars DeepBayes Summer School 2018
aliaksah/Effects-of-dietary-lipid-source-and-fish-size-on-steatosis-in-two-Atlantic-salmon-populations
supplementary materials
aliaksah/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.
aliaksah/portfolio
Personal webpage
aliaksah/R-worskhop
An intensive worksop for introduction to R
aliaksah/skweak
skweak: A software toolkit for weak supervision applied to NLP tasks
aliaksah/stin-300
selected lectures in spin 300
aliaksah/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
aliaksah/weak-supervision-for-NER
Framework to learn Named Entity Recognition models without labelled data using weak supervision.