Adaptive control on manifolds with RBF neural networks. - Valeri A. Terekhov; Ivan Yu. Tyukin; Danil V. Prokhorov (CDC, 2000)

On a problem of time-varying learning rate influence on the adaptive system dynamics. - Ivan Tyukin; Cees van Leeuwen; Danil V. Prokhorov; Valery A. Terekhov (CDC, 2002)

Finite form realizations of adaptive control algorithms. - Ivan Tyukin; Danil V. Prokhorov; Cees van Leeuwen (ECC, 2003)

Parameter Estimation of Sigmoid Superpositions: Dynamical System Approach. - Ivan Tyukin; Cees van Leeuwen; Danil V. Prokhorov (Neural Comput., 2003)

Adaptive control with nonconvex parameterization. - Ivan Tyukin; Danil V. Prokhorov; Valery A. Terekhov (IEEE Trans. Autom. Control., 2003)

A new method for adaptive brake control. - Ivan Tyukin; Danil V. Prokhorov; Cees van Leeuwen (ACC, 2005)

Invariant template matching in systems with spatiotemporal coding: a vote for instability - Ivan Tyukin; Tatiana Tyukina; Cees van Leeuwen (CoRR, 2007)

Adaptation and Parameter Estimation in Systems With Unstable Target Dynamics and Nonlinear Parametrization. - Ivan Tyukin; Danil V. Prokhorov; Cees van Leeuwen (IEEE Trans. Autom. Control., 2007)

Non-uniform small-gain theorems for systems with unstable invariant sets. - Ivan Tyukin; Erik Steur; Henk Nijmeijer; Cees van Leeuwen (CDC, 2008)

Adaptive Classification of Temporal Signals in Fixed-Weight Recurrent Neural Networks: An Existence Proof. - Ivan Tyukin; Danil V. Prokhorov; Cees van Leeuwen (Neural Comput., 2008)

Nonuniform Small-Gain Theorems for Systems with Unstable Invariant Sets. - Ivan Tyukin; Erik Steur; Henk Nijmeijer; Cees van Leeuwen (SIAM J. Control. Optim., 2008)

Feasibility of random basis function approximators for modeling and control. - Ivan Tyukin; Danil V. Prokhorov (CCA/ISIC, 2009)

Invariant template matching in systems with spatiotemporal coding: A matter of instability. - Ivan Tyukin; Tatiana Tyukina; Cees van Leeuwen (Neural Networks, 2009)

Supplement: The uncertainty principle of measurement in vision - Sergei Gepshtein; Ivan Tyukin; Thomas D. Albright (CoRR, 2010)

State and Parameter Estimation for Canonic Models of Neural oscillators. - Ivan Tyukin; Erik Steur; Henk Nijmeijer; David Fairhurst; Inseon Song; Alexey V. Semyanov; Cees van Leeuwen (Int. J. Neural Syst., 2010)

Explicit reduced-order integral formulations of state and parameter estimation problems for a class of nonlinear systems. - Ivan Tyukin; Alexander N. Gorban (CDC, 2013)

Adaptive observers and parameter estimation for a class of systems nonlinear in the parameters. - Ivan Tyukin; Erik Steur; Henk Nijmeijer; Cees van Leeuwen (Autom., 2013)

Lyapunov-like Conditions of Forward Invariance and Boundedness for a Class of Unstable Systems. - Alexander N. Gorban; Ivan Tyukin; Erik Steur; Henk Nijmeijer (SIAM J. Control. Optim., 2013)

Further results on Lyapunov-like conditions of forward invariance and boundedness for a class of unstable systems. - Alexander N. Gorban; Ivan Yu. Tyukin; Henk Nijmeijer (CDC, 2014)

Scene analysis assisting for AWB using binary decision trees and average image metrics. - Konstantin I. Sofeikov; Ilya V. Romanenko; Ivan Yu. Tyukin; Alexander N. Gorban (ICCE, 2014)

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)

Optimal measurement of visual motion across spatial and temporal scales. - Sergei Gepshtein; Ivan Tyukin (CoRR, 2014)

Phase Selective Oscillations in Two Noise Driven Synaptically Coupled Spiking Neurons. - Ilya Prokin; Ivan Tyukin; Victor B. Kazantsev (Int. J. Bifurc. Chaos, 2015)

The Blessing of Dimensionality: Separation Theorems in the Thermodynamic Limit. - Alexander N. Gorban; Ivan Yu. Tyukin; Ilya V. Romanenko (CoRR, 2016)

Approximation with random bases: Pro et Contra. - Alexander N. Gorban; Ivan Yu. Tyukin; Danil V. Prokhorov; Konstantin I. Sofeikov (Inf. Sci., 2016)

Stochastic separation theorems. - Alexander N. Gorban; Ivan Yu. Tyukin (Neural Networks, 2017)

Tackling Rare False-Positives in Face Recognition: A Case Study. - Sepehr Meshkinfamfard; Alexander N. Gorban; Ivan Tyukin (HPCC/SmartCity/DSS, 2018)

Efficiency of Shallow Cascades for Improving Deep Learning AI Systems. - Ivan Yu. Tyukin; Alexander N. Gorban; Danil V. Prokhorov; Stephen Green 001 (IJCNN, 2018)

Preface special issue on non-iterative approaches in learning. - Ponnuthurai N. Suganthan; Sushmita Mitra; Ivan Tyukin (Appl. Soft Comput., 2018)

Blessing of dimensionality: mathematical foundations of the statistical physics of data. - Alexander N. Gorban; Ivan Yu. Tyukin (CoRR, 2018)

Augmented Artificial Intelligence: a Conceptual Framework. - Alexander N. Gorban; Bogdan Grechuk; Ivan Yu. Tyukin (CoRR, 2018)

The unreasonable effectiveness of small neural ensembles in high-dimensional brain. - Alexander N. Gorban; Valeri A. Makarov; Ivan Yu. Tyukin (CoRR, 2018)

Knowledge Transfer Between Artificial Intelligence Systems. - Ivan Tyukin; Alexander N. Gorban; Konstantin I. Sofeykov; Ilya V. Romanenko (Frontiers Neurorobotics, 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)

Kernel Stochastic Separation Theorems and Separability Characterizations of Kernel Classifiers. - Ivan Yu. Tyukin; Alexander N. Gorban; Bogdan Grechuk; Stephen Green 001 (IJCNN, 2019)

Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics. - Stephen Green 001; Ivan Tyukin; Alexander N. Gorban (INNSBDDL, 2019)

Symphony of high-dimensional brain. - Alexander N. Gorban; Valeri A. Makarov; Ivan Yu. Tyukin (CoRR, 2019)

Blessing of dimensionality at the edge. - Ivan Yu. Tyukin; Alexander N. Gorban; Alistair A. McEwan; Sepehr Meshkinfamfard (CoRR, 2019)

One-trial correction of legacy AI systems and stochastic separation theorems. - Alexander N. Gorban; Richard Burton; Ilya V. Romanenko; Ivan Yu. Tyukin (Inf. Sci., 2019)

Fast construction of correcting ensembles for legacy Artificial Intelligence systems: Algorithms and a case study. - Ivan Yu. Tyukin; Alexander N. Gorban; Stephen Green 001; Danil V. Prokhorov (Inf. Sci., 2019)

Neural Networks for the Retrieval of Methane from the Sentinel-5 Precursor Satellite. - Rose Fenwick; Hartmut Boesch; Ivan Tyukin (IJCNN, 2020)

On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems. - Ivan Yu. Tyukin; Desmond J. Higham; Alexander N. Gorban (IJCNN, 2020)

Myocardial Infarction Detection and Quantification Based on a Convolution Neural Network with Online Error Correction Capabilities. - Shui-Hua Wang; Gerry P. McCann; Ivan Tyukin (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)

High-Dimensional Brain in a High-Dimensional World: Blessing of Dimensionality. - Alexander N. Gorban; Valery A. Makarov; Ivan Yu. Tyukin (Entropy, 2020)

Demystification of Few-shot and One-shot Learning. - Ivan Yu. Tyukin; Alexander N. Gorban; Muhammad H. Alkhudaydi; Qinghua Zhou (IJCNN, 2021)

Efficient state synchronisation in model-based testing through reinforcement learning. - Uraz Cengiz Türker; Robert M. Hierons; Mohammad Reza Mousavi 001; Ivan Yu. Tyukin (ASE, 2021)

The Feasibility and Inevitability of Stealth Attacks. - Ivan Yu. Tyukin; Desmond J. Higham; Eliyas Woldegeorgis; Alexander N. Gorban (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)

Advances in Data Preprocessing for Biomedical Data Fusion: An Overview of the Methods, Challenges, and Prospects. - Shuihua Wang; M. Emre Celebi 001; Yu-Dong Zhang 001; Xiang Yu; Siyuan Lu 001; Xujing Yao; Qinghua Zhou; Miguel Martinez-Garcia; Yingli Tian; Juan Manuel Górriz; Ivan Tyukin (Inf. Fusion, 2021)

Blessing of dimensionality at the edge and geometry of few-shot learning. - Ivan Yu. Tyukin; Alexander N. Gorban; Alistair A. McEwan; Sepehr Meshkinfamfard; Lixin Tang (Inf. Sci., 2021)

General stochastic separation theorems with optimal bounds. - Bogdan Grechuk; Alexander N. Gorban; Ivan Yu. Tyukin (Neural Networks, 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)

Learning from few examples with nonlinear feature maps. - Ivan Yu. Tyukin; Oliver J. Sutton; Alexander N. Gorban (CoRR, 2022)

Towards a mathematical understanding of learning from few examples with nonlinear feature maps. - Oliver J. Sutton; Alexander N. Gorban; Ivan Yu. Tyukin (CoRR, 2022)

A Geometric View on the Role of Nonlinear Feature Maps in Few-Shot Learning. - Oliver J. Sutton; Alexander N. Gorban; Ivan Yu. Tyukin (GSI (1), 2023)

The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning. - Alexander Bastounis; Alexander N. Gorban; Anders C. Hansen; Desmond J. Higham; Danil V. Prokhorov; Oliver J. Sutton; Ivan Yu. Tyukin; Qinghua Zhou (ICANN (1), 2023)

Relative Intrinsic Dimensionality Is Intrinsic to Learning. - Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Ivan Yu. Tyukin (ICANN (1), 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)

Neuromorphic tuning of feature spaces to overcome the challenge of low-sample high-dimensional data. - Qinghua Zhou; Oliver J. Sutton; Yudong Zhang 001; Alexander N. Gorban; Valeri A. Makarov; Ivan Yu. Tyukin (IJCNN, 2023)

Trustworthy Autonomous Systems Through Verifiability. - Mohammad Reza Mousavi 001; Ana Cavalcanti 001; Michael Fisher 001; Louise A. Dennis; Robert M. Hierons; Bilal Y. Kaddouh; Effie Lai-Chong Law; Robert C. Richardson; Jan Oliver Ringert; Ivan Tyukin; Jim Woodcock 001 (Computer, 2023)

MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images. - Shuihua Wang; Ahmed M. S. E. K. Abdelaty; Kelly Parke; Jayanth Ranjit Arnold; Gerry P. McCann; Ivan Yu. Tyukin (Entropy, 2023)

GeoAI in urban analytics. - Stefano De Sabbata; Andrea Ballatore; Harvey J. Miller; Renée Sieber; Ivan Tyukin; Godwin Yeboah (Int. J. Geogr. Inf. Sci., 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)

Stealth edits to large language models. - Oliver J. Sutton; Qinghua Zhou; Wei Wang 357; Desmond J. Higham; Alexander N. Gorban; Alexander Bastounis; Ivan Tyukin (NeurIPS, 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)

Agile gesture recognition for low-power applications: customisation for generalisation. - Ying Liu; Liucheng Guo; Valeri A. Makarov; Alexander Gorbana; Evgeny Mirkesa; Ivan Yu. Tyukin (CoRR, 2024)

Stealth edits for provably fixing or attacking large language models. - Oliver J. Sutton; Qinghua Zhou; Wei Wang 357; Desmond J. Higham; Alexander N. Gorban; Alexander Bastounis; Ivan Yu. Tyukin (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)

How adversarial attacks can disrupt seemingly stable accurate classifiers. - Oliver J. Sutton; Qinghua Zhou; Ivan Yu. Tyukin; Alexander N. Gorban; Alexander Bastounis; Desmond J. Higham (Neural Networks, 2024)

Accelerating Finite State Machine-Based Testing Using Reinforcement Learning. - Uraz Cengiz Türker; Robert M. Hierons; Khaled El-Fakih; Mohammad Reza Mousavi 001; Ivan Yu. Tyukin (IEEE Trans. Software Eng., 2024)

Knowledge-informed neuro-integrators for aggregation kinetics. - Dmitrii Lukashevich; Ivan Tyukin; Nikolai V. Brilliantov (Commun. Nonlinear Sci. Numer. Simul., 2024)

Situation-Based Neuromorphic Memory in Spiking Neuron-Astrocyte Network. - Susanna Yu Gordleeva; Yuliya Tsybina; Mikhail Krivonosov; Ivan Yu. Tyukin; Victor B. Kazantsev; Alexey Zaikin; Alexander N. Gorban (IEEE Trans. Neural Networks Learn. Syst., 2025)

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

StepProof: Step-by-step verification of natural language mathematical proofs. - Xiaolin Hu; Qinghua Zhou; Bogdan Grechuk; Ivan Yu. Tyukin (CoRR, 2025)

Staining and locking computer vision models without retraining. - Oliver J. Sutton; Qinghua Zhou; George Leete; Alexander N. Gorban; Ivan Yu. Tyukin (CoRR, 2025)