Dropout-Based Active Learning for Regression. - Evgenii Tsymbalov; Maxim Panov; Alexander Shapeev (AIST, 2018)

Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning. - Evgenii Tsymbalov; Sergei Makarychev; Alexander Shapeev; Maxim Panov (IJCAI, 2019)

A physics-informed AI method for calculating melting points with uncertainty control and optimal sampling. - Olga Klimanova; Timofei Miryashkin; Alexander Shapeev (CoRR, 2023)

Bayesian inference of composition-dependent phase diagrams. - Timofei Miryashkin; Olga Klimanova; Vladimir Ladygin; Alexander Shapeev (CoRR, 2023)

Resolving the Ti-V Phase Diagram Discrepancy with First-Principles Calculations and Bayesian Learning. - Timofei Miryashkin; Olga Klimanova; Alexander Shapeev (CoRR, 2025)