Vitaly Schetinin

68 papers B 8C 3Misc 1Journal 44Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bayesian Learning Strategies for Reducing Uncertainty of Decision-Making in Case of Missing Values. Mach. Learn. Knowl. Extr. Vitaly Schetinin, Livija Jakaite
2025	J	`jnl`	Explainable GMDH-type neural networks for decision making: Case of medical diagnostics. Appl. Soft Comput. Livia Jakaite, Vitaly Schetinin
2023	J	`jnl`	Adaptive Bayesian learning for making risk-aware decisions: A case of trauma survival prediction. Artif. Intell. Medicine Livia Jakaite, Vitaly Schetinin
2023	—	`conf`	The Batch Primary Components Transformer and Auto-Plasticity Learning Linear Units Architecture: Synthetic Image Generation Case. SNAMS Stanislav Selitskiy, Chihiro Inoue, Vitaly Schetinin, Livija Jakaite
2022	J	`jnl`	Review of Machine Learning Approach on Credit Card Fraud Detection. Hum. Centric Intell. Syst. Rejwan Bin Sulaiman, Vitaly Schetinin, Paul Sant
2021	—	`conf`	Deep Neural-Network Prediction for Study of Informational Efficiency. IntelliSys (2) Rejwan Bin Sulaiman, Vitaly Schetinin
2020	—	`ch.`	Deep Learning for Biometric Face Recognition: Experimental Study on Benchmark Data Sets. Deep Biometrics Natalya Selitskaya, Stanislaw Sielicki, Livia Jakaite, Vitaly Schetinin, F. Evans, Marc Conrad, Paul Sant
2018	J	`jnl`	Bayesian averaging over Decision Tree models for trauma severity scoring. Artif. Intell. Medicine Vitaly Schetinin, Livia Jakaite, Wojtek J. Krzanowski
2018	J	`jnl`	Bayesian averaging over decision tree models: An application for estimating uncertainty in trauma severity scoring. Int. J. Medical Informatics Vitaly Schetinin, Livia Jakaite, Wojtek J. Krzanowski
2018	J	`jnl`	Bayesian learning of models for estimating uncertainty in alert systems: Application to air traffic conflict avoidance. Integr. Comput. Aided Eng. Vitaly Schetinin, Livia Jakaite, Wojtek J. Krzanowski
2018	J	`jnl`	Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification. Int. J. Neural Syst. Vitaly Schetinin, Livia Jakaite, Ndifreke Nyah, Dusica Novakovic, Wojtek J. Krzanowski
2016	—	`conf`	Evolving polynomial neural networks for detecting abnormal patterns. IEEE Conf. on Intelligent Systems Ndifreke Nyah, Livia Jakaite, Vitaly Schetinin, Paul Sant, Amar Aggoun
2015	—	`conf`	Bayesian Predictive Modelling: Application to Aircraft Short-Term Conflict Alert System. BMA@UAI Vitaly Schetinin, Livia Jakaite, Wojtek J. Krzanowski
2014	—	`conf`	Computer-Aided Segmentation and Estimation of Indices in Brain CT Scans. MIUA Adnan Qureshi, Vitaly Schetinin
2013	J	`jnl`	Bayesian Decision Trees for predicting survival of patients: A study on the US National Trauma Data Bank. Comput. Methods Programs Biomed. Vitaly Schetinin, Livia Jakaite, Janis Jakaitis, Wojtek J. Krzanowski
2013	J	`jnl`	Prediction of survival probabilities with Bayesian Decision Trees. Expert Syst. Appl. Vitaly Schetinin, Livia Jakaite, Wojtek J. Krzanowski
2012	J	`jnl`	Bayesian Assessment of Newborn Brain Maturity from Two-Channel Sleep Electroencephalograms. Comput. Math. Methods Medicine Livia Jakaite, Vitaly Schetinin, Carsten Maple
2012	J	`jnl`	Classification of newborn EEG maturity with Bayesian averaging over decision trees. Expert Syst. Appl. Vitaly Schetinin, Livia Jakaite
2011	B	`conf`	Feature extraction from electroencephalograms for Bayesian assessment of newborn brain maturity. CBMS Livia Jakaite, Vitaly Schetinin, Joachim Schult
2011	B	`conf`	Informativeness of sleep cycle features in Bayesian assessment of newborn electroencephalographic maturation. CBMS Vitaly Schetinin, Livia Jakaite, Joachim Schult
2010	J	`jnl`	A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems CoRR Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2010	J	`jnl`	Feature Importance in Bayesian Assessment of Newborn Brain Maturity from EEG CoRR Livia Jakaite, Vitaly Schetinin, Carsten Maple
2008	J	`jnl`	An Evolutionary-Based Approach to Learning Multiple Decision Models from Underrepresented Data CoRR Vitaly Schetinin, Dayou Li, Carsten Maple
2008	—	`conf`	An Evolutionary-Based Approach to Learning Multiple Decision Models from Underrepresented Data. ICNC (1) Vitaly Schetinin, Dayou Li, Carsten Maple
2008	J	`jnl`	Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition. EURASIP J. Adv. Signal Process. Jegor Uglov, Livia Jakaite, Vitaly Schetinin, Carsten Maple
2008	J	`jnl`	Feature Selection for Bayesian Evaluation of Trauma Death Risk CoRR Livia Jakaite, Vitaly Schetinin
2007	—	`conf`	A Bayesian Model Averaging Methodology for Detecting EEG Artifacts. DSP Vitaly Schetinin, Carsten Maple
2007	—	`ch.`	Advanced Feature Recognition and Classification Using Artificial Intelligence Paradigms. Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images Vitaly Schetinin, Valentina V. Zharkova, Anatoly Brazhnikov, Sergei I. Zharkov, Emanuele Salerno, Luigi Bedini, Ercan E. Kuruoglu, Anna Tonazzini, Damjan Zazula, Boris Cigale, Hiroyuki Yoshida
2007	J	`jnl`	Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition CoRR Jegor Uglov, Vitaly Schetinin, Carsten Maple
2007	J	`jnl`	Confident Interpretation of Bayesian Decision Tree Ensembles for Clinical Applications. IEEE Trans. Inf. Technol. Biomed. Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Timothy J. Coats, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2007	—	`ch.`	Estimating Classification Uncertainty of Bayesian Decision TreeTechnique on Financial Data. Perception-based Data Mining and Decision Making in Economics and Finance Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2007	J	`jnl`	Representing classifier confidence in the safety critical domain: an illustration from mortality prediction in trauma cases. Neural Comput. Appl. Trevor C. Bailey, Richard M. Everson, Jonathan E. Fieldsend, Wojtek J. Krzanowski, Derek Partridge, Vitaly Schetinin
2007	B	`conf`	The Bayesian Decision Tree Technique Using an Adaptive Sampling Scheme. CBMS Vitaly Schetinin, Wojtek J. Krzanowski, Carsten Maple
2006	—	`ch.`	A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems. Integrated Intelligent Systems for Engineering Design Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2006	—	`conf`	Bayesian Decision Tree Averaging for the Probabilistic Interpretation of Solar Flare Occurrences. KES (3) Vitaly Schetinin, Valentina V. Zharkova, Sergei I. Zharkov
2006	C	`conf`	Classification with Confidence for Critical Systems. SSS Derek Partridge, Trevor C. Bailey, Richard M. Everson, Jonathan E. Fieldsend, Adolfo Hernández, Wojtek J. Krzanowski, Vitaly Schetinin
2006	J	`jnl`	Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique. J. Math. Model. Algorithms Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2006	J	`jnl`	Confidence in Classification: A Bayesian Approach. J. Classif. Wojtek J. Krzanowski, Trevor C. Bailey, Derek Partridge, Jonathan E. Fieldsend, Richard M. Everson, Vitaly Schetinin
2006	Misc	`conf`	Interpretability of Bayesian Decision Trees Induced from Trauma Data. ICAISC Derek Partridge, Vitaly Schetinin, Dayou Li, Timothy J. Coats, Jonathan E. Fieldsend, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey
2006	J	`jnl`	Learning polynomial networks for classification of clinical electroencephalograms. Soft Comput. Vitaly Schetinin, Joachim Schult
2006	C	`conf`	Optimising Data-Driven Safety Related Systems. SSS Richard M. Everson, Jonathan E. Fieldsend, Trevor C. Bailey, Wojtek J. Krzanowski, Derek Partridge, Vitaly Schetinin, Adolfo Hernández
2006	B	`conf`	Using A Bayesian Averaging Model for Estimating the Reliability of Decisions in Multimodal Biometrics. ARES Carsten Maple, Vitaly Schetinin
2005	J	`jnl`	A Learning Algorithm for Evolving Cascade Neural Networks CoRR Vitaly Schetinin
2005	J	`jnl`	A Neural Network Decision Tree for Learning Concepts from EEG Data CoRR Vitaly Schetinin
2005	J	`jnl`	A Neural-Network Technique for Recognition of Filaments in Solar Images CoRR Valentina V. Zharkova, Vitaly Schetinin
2005	J	`jnl`	A Neural-Network Technique to Learn Concepts from Electroencephalograms CoRR Vitaly Schetinin, Joachim Schult
2005	J	`jnl`	A neural-network technique to learn concepts from electroencephalograms. Theory Biosci. Vitaly Schetinin, Joachim Schult
2005	J	`jnl`	An Evolving Cascade Neural Network Technique for Cleaning Sleep Electroencephalograms CoRR Vitaly Schetinin
2005	J	`jnl`	Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique CoRR Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2005	J	`jnl`	Diagnostic Rule Extraction Using Neural Networks CoRR Vitaly Schetinin, Anatoly Brazhnikov
2005	J	`jnl`	Estimating Classification Uncertainty of Bayesian Decision Tree Technique on Financial Data CoRR Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2005	J	`jnl`	Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles CoRR Vitaly Schetinin, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Jonathan E. Fieldsend, Trevor C. Bailey, Adolfo Hernández
2005	J	`jnl`	Learning Multi-Class Neural-Network Models from Electroencephalograms CoRR Vitaly Schetinin, Joachim Schult, Burkhart Scheidt, Valery Kuriakin
2005	J	`jnl`	Learning Polynomial Networks for Classification of Clinical Electroencephalograms CoRR Vitaly Schetinin, Joachim Schult
2005	J	`jnl`	Learning from Web: Review of Approaches CoRR Vitaly Schetinin
2005	J	`jnl`	Neural-Network Techniques for Visual Mining Clinical Electroencephalograms CoRR Vitaly Schetinin, Joachim Schult, Anatoly Brazhnikov
2005	J	`jnl`	Polynomial Neural Networks Learnt to Classify EEG Signals CoRR Vitaly Schetinin
2005	J	`jnl`	Self-Organization of the Neuron Collective of Optimal Complexity CoRR Vitaly Schetinin, A. Kostunin
2005	J	`jnl`	Self-Organizing Multilayered Neural Networks of Optimal Complexity CoRR Vitaly Schetinin
2005	J	`jnl`	The Bayesian Decision Tree Technique with a Sweeping Strategy CoRR Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández
2005	J	`jnl`	The Combined Technique for Detection of Artifacts in Clinical Electroencephalograms of Sleeping Newborns CoRR Vitaly Schetinin, Joachim Schult
2004	C	`conf`	Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles. IDEAL Vitaly Schetinin, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Jonathan E. Fieldsend, Trevor C. Bailey, Adolfo Hernández
2004	J	`jnl`	The combined technique for detection of artifacts in clinical electroencephalograms of sleeping newborns. IEEE Trans. Inf. Technol. Biomed. Vitaly Schetinin, Joachim Schult
2003	J	`jnl`	A Learning Algorithm for Evolving Cascade Neural Networks. Neural Process. Lett. Vitaly Schetinin
2003	B	`conf`	A Neural-Network Technique for Recognition of Filaments in Solar Images. KES Valentina V. Zharkova, Vitaly Schetinin
2003	B	`conf`	A recognition of filaments in solar images with an artificial neural network. ESANN Valentina V. Zharkova, Vitaly Schetinin
2003	B	`conf`	Learning Multi-class Neural-Network Models from Electroencephalograms. KES Vitaly Schetinin, Joachim Schult, Burkhart Scheidt, Valery Kuriakin
2003	B	`conf`	Using Artificial Neural Networks for Combustion Interferometry. KES Victor Abrukov, Vitaly Schetinin, Pavel Deltsov