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Aliaksandr Hubin
Aliaksandr Hubin
PhD, Associate Professor, University of Oslo, NMBU, OUC
Verified email at math.uio.no - Homepage
Title
Cited by
Cited by
Year
Named Entity Recognition without Labelled Data: A Weak Supervision Approach
P Lison, J Barnes, A Hubin, S Touileb
58th Annual Meeting of the Association for Computational Linguistics, ISBN …, 2020
1162020
skweak: Weak Supervision Made Easy for NLP
P Lison, J Barnes, A Hubin
Proceedings of The Joint Conference of the 59th Annual Meeting of the …, 2021
422021
Estimating the marginal likelihood with Integrated nested Laplace approximation (INLA)
A Hubin, G Storvik
Technical report, doi.org/10.48550/arXiv.1611.01450, 2016
362016
Mode jumping MCMC for Bayesian variable selection in GLMM
A Hubin, G Storvik
Computational Statistics & Data Analysis, 2018
332018
Flexible Bayesian Nonlinear Model Configuration
A Hubin, G Storvik, F Frommlet
Journal of Artificial Intelligence Research 72, 901-942, 2021
22*2021
A novel algorithmic approach to Bayesian Logic Regression (with Discussion)
A Hubin, G Storvik, F Frommlet
Bayesian Analysis 15 (1), 263-311, 2020
212020
Combining model and parameter uncertainty in Bayesian neural networks
A Hubin, G Storvik
Technical report, https://doi.org/10.48550/arXiv.1903.07594, 2019
152019
Efficient mode jumping MCMC for Bayesian variable selection in GLMM
A Hubin, G Storvik
Technical report, doi.org/10.48550/arXiv.1604.06398, 2016
102016
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models
A Hubin
Proceedings of the International Conference on Artificial Intelligence …, 2019
92019
Bayesian model configuration, selection and averaging in complex regression contexts
A Hubin
Series of dissertations submitted to the Faculty of Mathematics and Natural …, 2018
62018
A Bayesian binomial regression model with latent Gaussian processes for modelling DNA methylation
A Hubin, GO Storvik, PE Grini, MA Butenko
Austrian Journal of Statistics 49 (4), 46-56, 2020
52020
A subsampling approach for Bayesian model selection
J Lachmann, G Storvik, F Frommlet, A Hubin
International Journal of Approximate Reasoning, 2022
22022
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI
T Papamarkou, M Skoularidou, K Palla, L Aitchison, J Arbel, D Dunson, ...
arXiv preprint arXiv:2402.00809, 2024
12024
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows
L Skaaret-Lund, G Storvik, A Hubin
arXiv preprint arXiv:2305.03395, 2023
12023
Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty
A Hubin, G Storvik
arXiv preprint arXiv:2305.00934, 2023
12023
Bayesian binomial regression model with a latent Gaussian field for analysis of epigenetic data
A Hubin, G Storvik, P Grini, M Butenko
Computer Data Analysis and Modeling: Stochastics and Data Science : Proc. of …, 2019
12019
Sparse Bayesian Neural Networks: Bridging Model and Parameter Uncertainty through Scalable Variational Inference
A Hubin, G Storvik
Mathematics 12 (6), 788, 2024
2024
Subsampling MCMC for Bayesian Variable Selection and Model Averaging in BGNLM
J Lachmann, A Hubin
arXiv preprint arXiv:2312.16997, 2023
2023
FBMS: Flexible Bayesian Model Selection and Model Averaging
J Lachmann, A Hubin, F Frommlet, G Storvik
https://cran.r-project.org/web/packages/FBMS/FBMS.pdf, 2023
2023
Fractional Polynomials Models as Special Cases of Bayesian Generalized Nonlinear Models
A Hubin, G Heinze, R De Bin
Fractal and Fractional 7 (9), 2023
2023
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