High order orthogonal tensor networks: information capacity and reliability. - Alexander N. Gorban; Yeugenii M. Mirkes; Donald C. Wunsch II (ICNN, 1997)

Generation of explicit knowledge from empirical data through pruning of trainable neural networks. - Alexander N. Gorban; Evgeny M. Mirkes; Victor G. Tsaregorodtsev (IJCNN, 1999)

Protective Laminar Composites Design Optimisation Using Genetic Algorithm and Parallel Processing. - Mikhail Alexandrovich Vishnevsky; Vladimir Dmitrievich Koshur; Alexander Ivanovich Legalov; Eugenij Moiseevich Mirkes (PaCT, 2003)

Initialization of Self-Organizing Maps: Principal Components Versus Random Initialization. A Case Study - A. A. Akinduko; Evgeny M. Mirkes (CoRR, 2012)

Geometrical Complexity of Data Approximators. - Evgeny M. Mirkes; Andrei Yu. Zinovyev; Alexander N. Gorban (IWANN (1), 2013)

New Structure in Genomes Manifests in Triplet Distribution Alongside a Sequence. - Michael G. Sadovsky; Eugene Mirkes (IWBBIO, 2013)

Data complexity measured by principal graphs. - Andrei Yu. Zinovyev; Evgeny M. Mirkes (Comput. Math. Appl., 2013)

Learning optimization for decision tree classification of non-categorical data with information gain impurity criterion. - Konstantin I. Sofeikov; Ivan Tyukin; Alexander N. Gorban; Eugenij Moiseevich Mirkes; Danil V. Prokhorov; Ilya V. Romanenko (IJCNN, 2014)

Computational diagnosis and risk evaluation for canine lymphoma. - Eugenij Moiseevich Mirkes; I. Alexandrakis; K. Slater; R. Tuli; Alexander N. Gorban (Comput. Biol. Medicine, 2014)

Handling missing data in large healthcare dataset: A case study of unknown trauma outcomes. - Eugenij Moiseevich Mirkes; Timothy J. Coats; Jeremy Levesley; Alexander N. Gorban (Comput. Biol. Medicine, 2016)

Robust principal graphs for data approximation. - Alexander N. Gorban; Eugenij Moiseevich Mirkes; Andrei Yu. Zinovyev (CoRR, 2016)

Piece-wise quadratic lego set for constructing arbitrary error potentials and their fast optimization. - Alexander N. Gorban; Eugenij Moiseevich Mirkes; Andrei Yu. Zinovyev (CoRR, 2016)

SOM: Stochastic initialization versus principal components. - Ayodeji A. Akinduko; Evgeny M. Mirkes; Alexander N. Gorban (Inf. Sci., 2016)

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning. - Alexander N. Gorban; Eugenij Moiseevich Mirkes; Andrei Yu. Zinovyev (Neural Networks, 2016)

Data analysis with arbitrary error measures approximated by piece-wise quadratic PQSQ functions. - Alexander N. Gorban; Evgeny M. Mirkes; Andrei Yu. Zinovyev (IJCNN, 2018)

Robust and scalable learning of data manifolds with complex topologies via ElPiGraph. - Luca Albergante; Evgeny M. Mirkes; Huidong Chen; Alexis Martin; Louis Faure; Emmanuel Barillot; Luca Pinello; Alexander N. Gorban; Andrei Yu. Zinovyev (CoRR, 2018)

How deep should be the depth of convolutional neural networks: a backyard dog case study. - Alexander N. Gorban; Evgeny M. Mirkes; I. Y. Tukin (CoRR, 2018)

Automatic Short Answer Grading and Feedback Using Text Mining Methods. - Neslihan Suzen; Alexander N. Gorban; Jeremy Levesley; Evgeny M. Mirkes (CoRR, 2018)

Correction of AI systems by linear discriminants: Probabilistic foundations. - Alexander N. Gorban; A. Golubkov; Bogdan Grechuk; Eugenij Moiseevich Mirkes; Ivan Tyukin (Inf. Sci., 2018)

Do Fractional Norms and Quasinorms Help to Overcome the Curse of Dimensionality? - Evgeny M. Mirkes; Jeza Allohibi; Alexander N. Gorban (IJCNN, 2019)

LScDC-new large scientific dictionary. - Neslihan Suzen; Evgeny M. Mirkes; Alexander N. Gorban (CoRR, 2019)

Towards a Portable Model to Discriminate Activity Clusters from Accelerometer Data. - Petra J. Jones; Evgeny M. Mirkes; Tom Yates; Charlotte L. Edwardson; Mike Catt; Melanie J. Davies; Kamlesh Khunti; Alex V. Rowlands (Sensors, 2019)

Artificial Neural Network Pruning to Extract Knowledge. - Evgeny M. Mirkes (IJCNN, 2020)

How Deep Should be the Depth of Convolutional Neural Networks: a Backyard Dog Case Study. - Alexander N. Gorban; Evgeny M. Mirkes; Ivan Yu. Tyukin (Cogn. Comput., 2020)

Informational Space of Meaning for Scientific Texts. - Neslihan Suzen; Evgeny M. Mirkes; Alexander N. Gorban (CoRR, 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)

Principal Components of the Meaning. - Neslihan Suzen; Alexander N. Gorban; Jeremy Levesley; Evgeny M. Mirkes (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)

Universal Gorban's Entropies: Geometric Case Study. - Evgeny M. Mirkes (Entropy, 2020)

Fractional Norms and Quasinorms Do Not Help to Overcome the Curse of Dimensionality. - Evgeny M. Mirkes; Jeza Allohibi; Alexander N. Gorban (Entropy, 2020)

GaussianProductAttributes: Density-Based Distributed Representations for Products. - Hossein Ghodrati Noushahr; Jeremy Levesley; Samad Ahmadi; Evgeny M. Mirkes (SGAI Conf., 2021)

Semantic Analysis for Automated Evaluation of the Potential Impact of Research Articles. - Neslihan Suzen; Alexander N. Gorban; Jeremy Levesley; Evgeny M. Mirkes (CoRR, 2021)

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

High-Dimensional Separability for One- and Few-Shot Learning. - Alexander N. Gorban; Bogdan Grechuk; Evgeny M. Mirkes; Sergey V. Stasenko; Ivan Yu. Tyukin (Entropy, 2021)

Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery. - Santos J. Núñez Jareño; Daniël P. van Helden; Evgeny M. Mirkes; Ivan Yu. Tyukin; Penelope M. Allison (Entropy, 2021)

CNN-Based Spectral Super-Resolution of Panchromatic Night-Time Light Imagery: City-Size-Associated Neighborhood Effects. - Natalya A. Rybnikova; Evgeny M. Mirkes; Alexander N. Gorban (Sensors, 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)

An Informational Space Based Semantic Analysis for Scientific Texts. - Neslihan Suzen; Alexander N. Gorban; Jeremy Levesley; Evgeny M. Mirkes (CoRR, 2022)

Coloring Panchromatic Nighttime Satellite Images: Comparing the Performance of Several Machine Learning Methods. - Natalya A. Rybnikova; Boris A. Portnov; Evgeny M. Mirkes; Andrei Yu. Zinovyev; Anna Brook; Alexander N. Gorban (IEEE Trans. Geosci. Remote. Sens., 2022)

What is Hiding in Medicine's Dark Matter? Learning with Missing Data in Medical Practices. - Neslihan Suzen; Evgeny M. Mirkes; Damian Roland; Jeremy Levesley; Alexander N. Gorban; Timothy J. Coats (IEEE Big Data, 2023)

Agile gesture recognition for capacitive sensing devices: adapting on-the-job. - Ying Liu; Liucheng Guo; Valeri A. Makarov; Yuxiang Huang; Alexander N. Gorban; Evgeny M. Mirkes; Ivan Yu. Tyukin (IJCNN, 2023)

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)

Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. - Ivan Yu. Tyukin; Tatiana Tyukina; Daniel van Helden; Zedong Zheng; Evgeny M. Mirkes; Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Penelope M. Allison (IJCNN, 2024)

Exploring the impact of social stress on the adaptive dynamics of COVID-19: Typing the behavior of naïve populations faced with epidemics. - Innokentiy Kastalskiy; Andrei Yu. Zinovyev; Evgeny M. Mirkes; Victor B. Kazantsev; Alexander N. Gorban (Commun. Nonlinear Sci. Numer. Simul., 2024)

Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. - Ivan Yu. Tyukin; Tatiana Tyukina; Daniël P. van Helden; Zedong Zheng; Evgeny M. Mirkes; Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Penelope M. Allison (CoRR, 2024)

Coping with AI errors with provable guarantees. - Ivan Yu. Tyukin; Tatiana Tyukina; Daniël P. van Helden; Zedong Zheng; Evgeny M. Mirkes; Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Penelope M. Allison (Inf. Sci., 2024)

Linear Dimensionality Reduction: What Is Better? - Mohit Baliyan; Evgeny M. Mirkes (Data, 2025)

When fractional quasi p-norms concentrate. - Ivan Yu. Tyukin; Bogdan Grechuk; Evgeny M. Mirkes; Alexander N. Gorban (CoRR, 2025)

Robust Deep Learning for Myocardial Scar Segmentation in Cardiac MRI with Noisy Labels. - Aida Moafi; Danial Moafi; Evgeny M. Mirkes; Gerry P. McCann; Abbas S. Alatrany; Jayanth Ranjit Arnold; Mostafa Mehdipour-Ghazi (CoRR, 2025)