| 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 | 152 | 2020 |
| 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 | 101* | 2024 |
| 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 | 63 | 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 | 48 | 2016 |
| Mode jumping MCMC for Bayesian variable selection in GLMM A Hubin, G Storvik Computational Statistics & Data Analysis, 2018 | 39 | 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 | 25 | 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 | 15 | 2019 |
| Sparse Bayesian Neural Networks: Bridging Model and Parameter Uncertainty through Scalable Variational Inference A Hubin, G Storvik Mathematics 12 (6), 788, 2024 | 13* | 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 |
| 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 | 7 | 2020 |
| 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 |
| 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 | 6 | 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 | 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 |
| 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 | 5 | 2024 |
| A subsampling approach for Bayesian model selection J Lachmann, G Storvik, F Frommlet, A Hubin International Journal of Approximate Reasoning, 2022 | 5 | 2022 |
| Fractional Polynomials Models as Special Cases of Bayesian Generalized Nonlinear Models A Hubin, G Heinze, R De Bin Fractal and Fractional 7 (9), 2023 | 4 | 2023 |
| Development and internal validation of a simple clinical score for the estimation of the probability of deep vein thrombosis in outpatient emergency department patients TD Halstensen, C Hardeland, W Ghanima, VA Grøndahl, A Hubin, ... Research and Practice in Thrombosis and Haemostasis 8 (8), 102608, 2024 | 3 | 2024 |
Geir StorvikProfessor in Statistics, University of OsloVerified email at math.uio.no
