Aliaksandr Hubin

23 papers A* 3Journal 18Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Sleep-Based Homeostatic Regularization for Stabilizing Spike-Timing-Dependent Plasticity in Recurrent Spiking Neural Networks.
CoRR
Andreas Massey, Aliaksandr Hubin, Stefano Nichele, Solve Sæbø
2026 J jnl
The role of voice and silence behaviors in software development: a structural equation modeling analysis.
Inf. Softw. Technol.
Mary Sánchez-Gordón, Ricardo Colomo-Palacios, Alex Sánchez Gordon, Aliaksandr Hubin
2025 J jnl
Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks.
CoRR
Eirik Høyheim, Lars Skaaret-Lund, Solve Sæbø, Aliaksandr Hubin
2025 J jnl
FBMS: An R Package for Flexible Bayesian Model Selection and Model Averaging.
CoRR
Florian Frommlet, Jon Lachmann, Geir Storvik, Aliaksandr Hubin
2025 J jnl
The effect of stereotypes on perceived competence of indigenous software practitioners: a study of dress style in professional photos.
Empir. Softw. Eng.
Mary Sánchez-Gordón, Ricardo Colomo-Palacios, Cathy Pamela Guevara-Vega, Antonio Quiña-Mera, Aliaksandr Hubin
2024 J jnl
Evolutionary variational inference for Bayesian generalized nonlinear models.
Neural Comput. Appl.
Philip Sebastian Hauglie Sommerfelt, Aliaksandr Hubin
2024 A* conf
Incorporating probabilistic domain knowledge into deep multiple instance learning.
ICML
Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri, Milena Pavlovic, Knut Dagestad Rand, Michael Widrich, Anne H. Schistad Solberg, Victor Greiff, Johan Pensar, Günter Klambauer, Geir Kjetil Sandve
2024 J jnl
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.
CoRR
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
2024 A* conf
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI.
ICML
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
2024 J jnl
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows.
Trans. Mach. Learn. Res.
Lars Skaaret-Lund, Geir Storvik, Aliaksandr Hubin
2023 J jnl
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows.
CoRR
Lars Skaaret-Lund, Geir Storvik, Aliaksandr Hubin
2023 J jnl
Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty.
CoRR
Aliaksandr Hubin, Geir Storvik
2022 J jnl
A subsampling approach for Bayesian model selection.
Int. J. Approx. Reason.
Jon Lachmann, Geir Storvik, Florian Frommlet, Aliaksandr Hubin
2021 J jnl
Flexible Bayesian Nonlinear Model Configuration.
J. Artif. Intell. Res.
Aliaksandr Hubin, Geir Storvik, Florian Frommlet
2021 — conf
skweak: Weak Supervision Made Easy for NLP.
ACL (demo)
Pierre Lison, Jeremy Barnes, Aliaksandr Hubin
2021 J jnl
skweak: Weak Supervision Made Easy for NLP.
CoRR
Pierre Lison, Jeremy Barnes, Aliaksandr Hubin
2020 J jnl
Flexible Bayesian Nonlinear Model Configuration.
CoRR
Aliaksandr Hubin, Geir Storvik, Florian Frommlet
2020 A* conf
Named Entity Recognition without Labelled Data: A Weak Supervision Approach.
ACL
Pierre Lison, Jeremy Barnes, Aliaksandr Hubin, Samia Touileb
2020 J jnl
Named Entity Recognition without Labelled Data: A Weak Supervision Approach.
CoRR
Pierre Lison, Aliaksandr Hubin, Jeremy Barnes, Samia Touileb
2019 — conf
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models.
AIIPCC
Aliaksandr Hubin
2019 J jnl
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models.
CoRR
Aliaksandr Hubin
2019 J jnl
Combining Model and Parameter Uncertainty in Bayesian Neural Networks.
CoRR
Aliaksandr Hubin, Geir Storvik
2018 J jnl
Mode jumping MCMC for Bayesian variable selection in GLMM.
Comput. Stat. Data Anal.
Aliaksandr Hubin, Geir Storvik