| 2022 | IJCNN | Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation. | Qinghua Zhou, Alexander N. Gorban, Evgeny M. Mirkes, Jonathan Bac, Andrei Yu. Zinovyev, Ivan Yu. Tyukin |
| 2021 | IJCNN | Clinical trajectories estimated from bulk tumoral molecular profiles using elastic principal trees. | Alexander Chervov, Andrei Yu. Zinovyev |
| 2020 | IJCNN | Local intrinsic dimensionality estimators based on concentration of measure. | Jonathan Bac, Andrei Yu. Zinovyev |
| 2019 | IJCNN | Estimating the effective dimension of large biological datasets using Fisher separability analysis. | Luca Albergante, Jonathan Bac, Andrei Yu. Zinovyev |
| 2019 | ICTAI | Synthesis of Boolean Networks from Biological Dynamical Constraints using Answer-Set Programming. | Stphanie Chevalier, Christine Froidevaux, Loc Paulev, Andrei Yu. Zinovyev |
| 2018 | IJCNN | Data analysis with arbitrary error measures approximated by piece-wise quadratic PQSQ functions. | Alexander N. Gorban, Evgeny M. Mirkes, Andrei Yu. Zinovyev |
| 2015 | DSAA | Fast and user-friendly non-linear principal manifold learning by method of elastic maps. | Alexander N. Gorban, Andrei Yu. Zinovyev |
| 2013 | IWANN | Geometrical Complexity of Data Approximators. | Evgeny M. Mirkes, Andrei Yu. Zinovyev, Alexander N. Gorban |
| 2007 | IJCNN | Branching Principal Components: Elastic Graphs, Topological Grammars and Metro Maps. | Alexander N. Gorban, Neil R. Sumner, Andrei Yu. Zinovyev |
| 2003 | IJCNN | Application of the method of elastic maps in analysis of genetic texts. | Alexander N. Gorban, Andrei Yu. Zinovyev, Donald C. Wunsch |