2 papers
cs.LG2026
Learning Chern Numbers of Topological Insulators with Gauge Equivariant Neural Networks
Longde Huang, Oleksandr Balabanov, Hampus Linander +3
Equivariant network architectures are a well-established tool for predicting invariant or equivariant quantities. However, almost all learning problems considered in this context f…
cs.LG2025
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles
Oleksandr Balabanov, Hampus Linander
Fine-tuning large language models can improve task specific performance, although a general understanding of what the fine-tuned model has learned, forgotten and how to trust its p…