Estimating the effective dimension of large biological datasets using Fisher separability analysis. - Luca Albergante; Jonathan Bac; Andrei Yu. Zinovyev (IJCNN, 2019)

Lizard Brain: Tackling Locally Low-Dimensional Yet Globally Complex Organization of Multi-Dimensional Datasets. - Jonathan Bac; Andrei Yu. Zinovyev (Frontiers Neurorobotics, 2019)

Local intrinsic dimensionality estimators based on concentration of measure. - Jonathan Bac; Andrei Yu. Zinovyev (IJCNN, 2020)

Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data. - Sergey E. Golovenkin; Jonathan Bac; Alexander Chervov; Evgeny M. Mirkes; Yuliya V. Orlova; Emmanuel Barillot; Alexander N. Gorban; Andrei Yu. Zinovyev (CoRR, 2020)

Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph. - Luca Albergante; Evgeny M. Mirkes; Jonathan Bac; Huidong Chen; Alexis Martin; Louis Faure; Emmanuel Barillot; Luca Pinello; Alexander N. Gorban; Andrei Yu. Zinovyev (Entropy, 2020)

Minimum Spanning vs. Principal Trees for Structured Approximations of Multi-Dimensional Datasets. - Alexander Chervov; Jonathan Bac; Andrei Yu. Zinovyev (Entropy, 2020)

Scikit-Dimension: A Python Package for Intrinsic Dimension Estimation. - Jonathan Bac; Evgeny M. Mirkes; Alexander N. Gorban; Ivan Tyukin; Andrei Yu. Zinovyev (Entropy, 2021)

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 (IJCNN, 2022)

Hubness reduction improves clustering and trajectory inference in single-cell transcriptomic data. - Elise Amblard; Jonathan Bac; Alexander Chervov; Vassili Soumelis; Andrei Yu. Zinovyev (Bioinform., 2022)

Domain Adaptation Principal Component Analysis: Base Linear Method for Learning with Out-of-Distribution Data. - Evgeny M. Mirkes; Jonathan Bac; Aziz Fouché; Sergey V. Stasenko; Andrei Yu. Zinovyev; Alexander N. Gorban (Entropy, 2023)