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 | 134 | 2020 |
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 | 57 | 2021 |
Estimating the marginal likelihood with Integrated nested Laplace approximation (INLA) A Hubin, G Storvik Technical report, doi.org/10.48550/arXiv.1611.01450, 2016 | 42 | 2016 |
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI T Papamarkou, M Skoularidou, K Palla, L Aitchison, J Arbel, D Dunson, ... Forty-first International Conference on Machine Learning, 2024 | 41* | 2024 |
Mode jumping MCMC for Bayesian variable selection in GLMM A Hubin, G Storvik Computational Statistics & Data Analysis, 2018 | 33 | 2018 |
Flexible Bayesian Nonlinear Model Configuration A Hubin, G Storvik, F Frommlet Journal of Artificial Intelligence Research 72, 901-942, 2021 | 27* | 2021 |
A novel algorithmic approach to Bayesian Logic Regression (with Discussion) A Hubin, G Storvik, F Frommlet Bayesian Analysis 15 (1), 263-311, 2020 | 22 | 2020 |
Combining model and parameter uncertainty in Bayesian neural networks A Hubin, G Storvik Technical report, https://doi.org/10.48550/arXiv.1903.07594, 2019 | 19 | 2019 |
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 | 11 | 2019 |
Sparse Bayesian Neural Networks: Bridging Model and Parameter Uncertainty through Scalable Variational Inference A Hubin, G Storvik Mathematics 12 (6), 788, 2024 | 10* | 2024 |
Efficient mode jumping MCMC for Bayesian variable selection in GLMM A Hubin, G Storvik Technical report, doi.org/10.48550/arXiv.1604.06398, 2016 | 10 | 2016 |
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows L Skaaret-Lund, G Storvik, A Hubin Transactions on Machine Learning Research (TMLR), 1-32, 2024 | 6 | 2024 |
Bayesian model configuration, selection and averaging in complex regression contexts A Hubin Series of dissertations submitted to the Faculty of Mathematics and Natural …, 2018 | 6 | 2018 |
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 | 5 | 2020 |
Fractional Polynomials Models as Special Cases of Bayesian Generalized Nonlinear Models A Hubin, G Heinze, R De Bin Fractal and Fractional 7 (9), 2023 | 3 | 2023 |
A subsampling approach for Bayesian model selection J Lachmann, G Storvik, F Frommlet, A Hubin International Journal of Approximate Reasoning, 2022 | 3 | 2022 |
Motor effects of fentanyl in isoflurane-anaesthetized pigs and the subsequent effect of ketanserin or naloxone N Digranes, E Hoeberg, A Lervik, A Hubin, J Nordgreen, HA Haga Veterinary Anaesthesia and Analgesia 51 (5), 491-499, 2024 | 1 | 2024 |
Effects of dietary fish to rapeseed oil ratio on steatosis symptoms in Atlantic salmon (Salmo salar L) of different sizes D Siciliani, A Hubin, B Ruyter, EM Chikwati, VG Thunes, EC Valen, ... Scientific Reports 14 (1), 18006, 2024 | 1 | 2024 |
Incorporating probabilistic domain knowledge into deep multiple instance learning GS Al Hajj, A Hubin, C Kanduri, M Pavlovic, KD Rand, M Widrich, ... Forty-first International Conference on Machine Learning, 2024 | 1 | 2024 |
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 | 1 | 2019 |