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Aliaksandr Hubin
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2020 – today
- 2024
- [i8]Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang:
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR abs/2402.00809 (2024) - 2023
- [i7]Aliaksandr Hubin, Geir Storvik:
Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty. CoRR abs/2305.00934 (2023) - [i6]Lars Skaaret-Lund, Geir Storvik, Aliaksandr Hubin:
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows. CoRR abs/2305.03395 (2023) - 2022
- [j3]Jon Lachmann, Geir Storvik, Florian Frommlet, Aliaksandr Hubin
:
A subsampling approach for Bayesian model selection. Int. J. Approx. Reason. 151: 33-63 (2022) - 2021
- [j2]Aliaksandr Hubin
, Geir Storvik, Florian Frommlet
:
Flexible Bayesian Nonlinear Model Configuration. J. Artif. Intell. Res. 72: 901-942 (2021) - [c3]Pierre Lison, Jeremy Barnes, Aliaksandr Hubin:
skweak: Weak Supervision Made Easy for NLP. ACL (demo) 2021: 337-346 - [i5]Pierre Lison, Jeremy Barnes, Aliaksandr Hubin:
skweak: Weak Supervision Made Easy for NLP. CoRR abs/2104.09683 (2021) - 2020
- [c2]Pierre Lison, Jeremy Barnes, Aliaksandr Hubin, Samia Touileb:
Named Entity Recognition without Labelled Data: A Weak Supervision Approach. ACL 2020: 1518-1533 - [i4]Aliaksandr Hubin, Geir Storvik, Florian Frommlet:
Flexible Bayesian Nonlinear Model Configuration. CoRR abs/2003.02929 (2020) - [i3]Pierre Lison, Aliaksandr Hubin, Jeremy Barnes, Samia Touileb:
Named Entity Recognition without Labelled Data: A Weak Supervision Approach. CoRR abs/2004.14723 (2020)
2010 – 2019
- 2019
- [c1]Aliaksandr Hubin:
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models. AIIPCC 2019: 63:1-63:9 - [i2]Aliaksandr Hubin, Geir Storvik:
Combining Model and Parameter Uncertainty in Bayesian Neural Networks. CoRR abs/1903.07594 (2019) - [i1]Aliaksandr Hubin:
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models. CoRR abs/1912.09733 (2019) - 2018
- [j1]Aliaksandr Hubin, Geir Storvik:
Mode jumping MCMC for Bayesian variable selection in GLMM. Comput. Stat. Data Anal. 127: 281-297 (2018)
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