Unsupervised interpretable learning of topological indices invariant under permutations of atomic bands. - Oleksandr Balabanov; Mats Granath (Mach. Learn. Sci. Technol., 2021)

Looking at the posterior: on the origin of uncertainty in neural-network classification. - Hampus Linander; Oleksandr Balabanov; Henry Yang; Bernhard Mehlig (CoRR, 2022)

Bayesian Posterior Approximation With Stochastic Ensembles. - Oleksandr Balabanov; Bernhard Mehlig; Hampus Linander (CVPR, 2023)

Looking at the posterior: accuracy and uncertainty of neural-network predictions. - Hampus Linander; Oleksandr Balabanov; Henry Yang; Bernhard Mehlig (Mach. Learn. Sci. Technol., 2023)

Uncertainty quantification in fine-tuned LLMs using LoRA ensembles. - Oleksandr Balabanov; Hampus Linander (CoRR, 2024)

Learning Chern Numbers of Topological Insulators with Gauge Equivariant Neural Networks. - Longde Huang; Oleksandr Balabanov; Hampus Linander; Mats Granath; Daniel Persson; Jan E. Gerken (CoRR, 2025)