B. Gabrys

Katarzyna Musial, Dongxiao He, Bogdan Gabrys, 2017, 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Analysis of Uncertainties in Water Systems Using Neural Networks

Andrzej Bargiela, Bogdan Gabrys, A. Bargiela, 1999 .

Autonomous overlapping community detection in temporal networks: A dynamic Bayesian nonnegative matrix factorization approach

Dongxiao He, Bogdan Gabrys, Pengfei Jiao, 2016, Knowl. Based Syst..

Learning with Missing or Incomplete Data

Bogdan Gabrys, B. Gabrys, 2009, ICIAP.

Sequential Approaches for Predicting Business Process Outcome and Process Failure Warning

Detlef D. Nauck, Bogdan Gabrys, Mai Le, 2013, SIMPDA.

Metalearning: a survey of trends and technologies

Bogdan Gabrys, Marcin Budka, Christiane Lemke, 2013, Artificial Intelligence Review.

Data-driven Soft Sensors in the process industry

Bogdan Gabrys, Petr Kadlec, Sibylle Strandt, 2009, Comput. Chem. Eng..

Robust Detection of Communities with Multi-semantics in Large Attributed Networks

Katarzyna Musial, Dongxiao He, Bogdan Gabrys, 2018, KSEM.

Classifier selection for majority voting

Bogdan Gabrys, Dymitr Ruta, D. Ruta, 2005, Inf. Fusion.

Clustering for Data Matching

Edward Tersoo Apeh, Bogdan Gabrys, B. Gabrys, 2006, KES.

Automatic Composition and Optimization of Multicomponent Predictive Systems With an Extended Auto-WEKA

Bogdan Gabrys, Marcin Budka, Manuel Martin Salvador, 2016, IEEE Transactions on Automation Science and Engineering.

Automatic composition and optimisation of multicomponent predictive systems pdf

Bogdan Gabrys, Marcin Budka, Manuel Martin Salvador, 2016, ArXiv.

An Improved Online Learning Algorithm for General Fuzzy Min-Max Neural Network

Bogdan Gabrys, T. T. Khuat, Fang Chen, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

A comparative study of general fuzzy min-max neural networks for pattern classification problems pdf

Bogdan Gabrys, T. T. Khuat, Thanh Tung Khuat, 2019, Neurocomputing.

Adaptive Mechanisms for Classification Problems with Drifting Data

Paul Rogers, Bogdan Gabrys, Abdelhamid Bouchachia, 2007, KES.

Overview of Some Incremental Learning Algorithms

Bogdan Gabrys, Abdelhamid Bouchachia, Zoheir Sahel, 2007, 2007 IEEE International Fuzzy Systems Conference.

Investigation of Expert Addition Criteria for Dynamically Changing Online Ensemble Classifiers with Multiple Adaptive Mechanisms

Bogdan Gabrys, Rashid Bakirov, B. Gabrys, 2013, AIAI.

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

B. Gabrys, Katarzyna Musial, Xuanyi Dong, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

On Accuracy of PDF Divergence Estimators and Their Applicability to Representative Data Sampling

Katarzyna Musial, Bogdan Gabrys, Marcin Budka, 2011, Entropy.

Electrostatic field framework for supervised and semi-supervised learning from incomplete data

Bogdan Gabrys, Marcin Budka, B. Gabrys, 2011, Natural Computing.

Toward Digital Twin Oriented Modeling of Complex Networked Systems and Their Dynamics: A Comprehensive Survey

B. Gabrys, Katarzyna Musial, Jiaqi Wen, 2022, IEEE Access.

Measuring Quadrangle Formation in Complex Networks pdf

Katarzyna Musial, Bogdan Gabrys, Mingshan Jia, 2020, IEEE Transactions on Network Science and Engineering.

Analysing Ego-Networks via Typed-Edge Graphlets: A Case Study of Chronic Pain Patients

B. Gabrys, Katarzyna Musial, L. Goubert, 2021, COMPLEX NETWORKS.

Review of adaptation mechanisms for data-driven soft sensors

Bogdan Gabrys, Ratko Grbic, Petr Kadlec, 2011, Comput. Chem. Eng..

Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction

Katarzyna Musial, Bogdan Gabrys, Hongzhi Yin, 2020, KDD.

Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey

Katarzyna Musial, Bogdan Gabrys, Joakim Skarding, 2020, IEEE Access.

Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems

Bogdan Gabrys, B. Gabrys, 2002, Int. J. Approx. Reason..

Automated Machine Learning Techniques in Prognostics of Railway Track Defects

Bogdan Gabrys, Simon Kocbek, Simon Kocbek, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

Forty years of computers & chemical engineering: A bibliometric analysis

Bogdan Gabrys, Jay H. Lee, Jay H. Lee, 2020, Comput. Chem. Eng..

AutoHAS: Differentiable Hyper-parameter and Architecture Search pdf

Quoc V. Le, Bogdan Gabrys, Adams Wei Yu, 2020, ArXiv.

Predicting Multi-class Customer Profiles Based on Transactions: a Case Study in Food Sales

Mykola Pechenizkiy, Edward Tersoo Apeh, Bogdan Gabrys, 2012, SGAI Conf..

Detecting and Visualizing the Change in Classification of Customer Profiles based on Transactional Data

Edward Tersoo Apeh, Bogdan Gabrys, B. Gabrys, 2012, Evolving Systems.

Learnt Topology Gating Artificial Neural Networks

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

AutoHAS: Efficient Hyperparameter and Architecture Search.

Quoc V. Le, Bogdan Gabrys, Adams Wei Yu, 2020 .

The security challenges in the IoT enabled cyber-physical systems and opportunities for evolutionary computing & other computational intelligence

Ashutosh Tiwari, Tim Watson, Yaochu Jin, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Customer profile classification using transactional data

Edward Tersoo Apeh, Bogdan Gabrys, Amanda C. Schierz, 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

Meta-learning for time series forecasting and forecast combination

Bogdan Gabrys, Christiane Lemke, B. Gabrys, 2010, Neurocomputing.

On sequences of different adaptive mechanisms in non-stationary regression problems

Damien Fay, Bogdan Gabrys, Rashid Bakirov, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Density-Preserving Sampling: Robust and Efficient Alternative to Cross-Validation for Error Estimation

Bogdan Gabrys, Marcin Budka, B. Gabrys, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Automated adaptation strategies for stream learning

Damien Fay, Bogdan Gabrys, Rashid Bakirov, 2018, Machine Learning.

Generic adaptation strategies for automated machine learning pdf

Damien Fay, Bogdan Gabrys, Rashid Bakirov, 2018, ArXiv.

Customer profile classification: To adapt classifiers or to relabel customer profiles?

Edward Tersoo Apeh, Bogdan Gabrys, Amanda C. Schierz, 2014, Neurocomputing.

An overview of self-adaptive technologies within virtual reality training

Bogdan Gabrys, Venketesh N. Dubey, Neil Vaughan, 2016, Comput. Sci. Rev..

Effects of Change Propagation Resulting from Adaptive Preprocessing in Multicomponent Predictive Systems

Bogdan Gabrys, Marcin Budka, Manuel Martin Salvador, 2016, KES.

General fuzzy min-max neural network for clustering and classification

Andrzej Bargiela, Bogdan Gabrys, A. Bargiela, 2000, IEEE Trans. Neural Networks Learn. Syst..

Learning hybrid neuro-fuzzy classifier models from data: to combine or not to combine?

Bogdan Gabrys, B. Gabrys, 2004, Fuzzy Sets Syst..

Temporal Changes in Local Topology of an Email-Based Social Network

Katarzyna Musial, Krzysztof Juszczyszyn, Bogdan Gabrys, 2009, Comput. Informatics.

Local learning‐based adaptive soft sensor for catalyst activation prediction

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2011 .

A Review of Meta-level Learning in the Context of Multi-component, Multi-level Evolving Prediction Systems pdf

Bogdan Gabrys, Abbas Raza Ali, Marcin Budka, 2020, ArXiv.

Adapting Multicomponent Predictive Systems using Hybrid Adaptation Strategies with Auto-WEKA in Process Industry

Bogdan Gabrys, Marcin Budka, Manuel Martin Salvador, 2016, AutoML@ICML.

Next challenges for adaptive learning systems

Katarzyna Musial, Mohamed Medhat Gaber, João Gama, 2012, SKDD.

What kind of network are you? - Using local and global characteristics in network categorisation tasks

Katarzyna Musial, Bogdan Gabrys, Marcin Buczko, 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).

An overview of interactive visual data mining techniques for knowledge discovery

Mohamed Medhat Gaber, Bogdan Gabrys, Frederic T. Stahl, 2013, WIREs Data Mining Knowl. Discov..

Data Analytics Enhanced Data Visualization and Interrogation with Parallel Coordinates Plots

Bogdan Gabrys, Muhammad Sajjad Akbar, B. Gabrys, 2018, 2018 26th International Conference on Systems Engineering (ICSEng).

Directed closure coefficient and its patterns

B. Gabrys, Katarzyna Musial, Mingshan Jia, 2021, PloS one.

Detecting and Visualizing the Change in Classification of Customer Profiles based on Transactional Data

B. Gabrys, E. Apeh, 2013, Evolutionary Systematics.

Change Mining of Customer Profiles Based on Transactional Data

Edward Tersoo Apeh, Bogdan Gabrys, B. Gabrys, 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

Adaptive Preprocessing for Streaming Data

Bogdan Gabrys, Indre Zliobaite, I. Žliobaitė, 2014, IEEE Transactions on Knowledge and Data Engineering.

Closure Coefficient in Complex Directed Networks

B. Gabrys, Katarzyna Musial, Mingshan Jia, 2020, COMPLEX NETWORKS.

Patterns of Interactions in Complex Social Networks Based on Coloured Motifs Analysis

Katarzyna Musial, Krzysztof Juszczyszyn, Bogdan Gabrys, 2009, ICONIP.

Temporal Changes in Connection Patterns of an Email-Based Social Network

Katarzyna Musial, Krzysztof Juszczyszyn, Bogdan Gabrys, 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

Adaptive Local Learning Soft Sensor for Inferential Control Support

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2008, 2008 International Conference on Computational Intelligence for Modelling Control & Automation.

Sequential Clustering for Event Sequences and Its Impact on Next Process Step Prediction

Detlef D. Nauck, Bogdan Gabrys, Trevor P. Martin, 2014, IPMU.

Towards Meta-learning of Deep Architectures for Efficient Domain Adaptation

Bogdan Gabrys, Abbas Raza Ali, Marcin Budka, 2019, PRICAI.

The Roles and Modes of Human Interactions with Automated Machine Learning Systems

T. T. Khuat, B. Gabrys, D. Kedziora, 2022, ArXiv.

Exploring Opportunistic Meta-knowledge to Reduce Search Spaces for Automated Machine Learning

B. Gabrys, Katarzyna Musial, D. Kedziora, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Practical implementation of computationally-efficient machine learning-based control performance assessment system for a class of closed loop systems

T. T. Khuat, B. Gabrys, Jacek Czeczot, 2023, Appl. Soft Comput..

KNNs and Sequence Alignment for Churn Prediction

Detlef D. Nauck, Bogdan Gabrys, Trevor P. Martin, 2013, SGAI Conf..

Multiple adaptive mechanisms for data-driven soft sensors

Damien Fay, Bogdan Gabrys, Rashid Bakirov, 2017, Comput. Chem. Eng..

Application of Machine Learning to Performance Assessment for a Class of PID-Based Control Systems

T. T. Khuat, B. Gabrys, Jacek Czeczot, 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Combining neuro-fuzzy classifiers for improved generalisation and reliability

Bogdan Gabrys, B. Gabrys, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Do Smart Adaptive Systems Exist? - Introduction

B. Gabrys, B. Gabrys, 2005 .

Multicriteria approaches for predictive model generation: A comparative experimental study

Bogdan Gabrys, Bassma Al-Jubouri, B. Gabrys, 2014, 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM).

Comparing and Combining Time Series Trajectories Using Dynamic Time Warping

Bogdan Gabrys, Neil Vaughan, B. Gabrys, 2016, KES.

Reducing Spatial Data Complexity for Classification Models

Bogdan Gabrys, Dymitr Ruta, D. Ruta, 2007 .

Static Field Approach for Pattern Classification

Bogdan Gabrys, Dymitr Ruta, D. Ruta, 2002, Soft-Ware.

Application of Base Learners as Conditional Input for Fuzzy Rule-Based Combined System

Athanasios Tsakonas, Bogdan Gabrys, B. Gabrys, 2012, IJCCI.

Do we need experts for time series forecasting?

Bogdan Gabrys, Christiane Lemke, B. Gabrys, 2008, ESANN.

Pooling for Combination of Multilevel Forecasts

Bogdan Gabrys, Silvia Riedel, B. Gabrys, 2009, IEEE Transactions on Knowledge and Data Engineering.

The Dynamics of Negative Correlation Learning

Bogdan Gabrys, Mark Eastwood, B. Gabrys, 2007, J. VLSI Signal Process..

Maximum Likelihood Topology Preserving Ensembles

Emilio Corchado, Bogdan Gabrys, Bruno Baruque, 2006, IDEAL.

Combining labelled and unlabelled data in the design of pattern classification systems

Bogdan Gabrys, Lina Petrakieva, B. Gabrys, 2004, Int. J. Approx. Reason..

Digital Twin-Oriented Complex Networked Systems based on Heterogeneous node features and interaction rules

B. Gabrys, Katarzyna Musial, Jiaqi Wen, 2023, ArXiv.

Review and Assessment of Digital Twin–Oriented Social Network Simulators

B. Gabrys, Katarzyna Musial, Jiaqi Wen, 2023, IEEE Access.

The Challenge of Quickly Determining the Quality of a Single-Photon Source

B. Gabrys, D. Kedziora, A. Musiał, 2023, ArXiv.

Outlier Resistant PCA Ensembles

Emilio Corchado, Bogdan Gabrys, Bruno Baruque, 2006, KES.

From Sensor Readings to Predictions: On the Process of Developing Practical Soft Sensors

Athanasios Tsakonas, Bogdan Gabrys, Marcin Budka, 2014, IDA.

Adaptive on-line prediction soft sensing without historical data

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

The Technological Emergence of AutoML: A Survey of Performant Software and Applications in the Context of Industry

B. Gabrys, Katarzyna Musial, D. Kedziora, 2022, ArXiv.

AutoWeka4MCPS-AVATAR: Accelerating Automated Machine Learning Pipeline Composition and Optimisation pdf

Katarzyna Musial, Bogdan Gabrys, Tien-Dung Nguyen, 2020, Expert Syst. Appl..

An Effective Multiresolution Hierarchical Granular Representation Based Classifier Using General Fuzzy Min-Max Neural Network pdf

Fang Chen, Bogdan Gabrys, T. T. Khuat, 2019, IEEE Transactions on Fuzzy Systems.

Modelling Multi-Component Predictive Systems as Petri Nets

Bogdan Gabrys, Marcin Budka, Manuel Martin Salvador, 2017 .

Towards Automatic Composition of Multicomponent Predictive Systems

Bogdan Gabrys, Marcin Budka, Manuel Martin Salvador, 2016, HAIS.

Architecture for development of adaptive on-line prediction models

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2009, Memetic Comput..

Evolving on-line prediction model dealing with industrial data sets

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2009, 2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems.

Soft Sensor Based on Adaptive Local Learning

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2008, ICONIP.

Soft sensors: Where are we and what are the current and future challenges?

Bogdan Gabrys, Petr Kadlec, B. Gabrys, 2009, ICONS.

Using (Automated) Machine Learning and Drug Prescription Records to Predict Mortality and Polypharmacy in Older Type 2 Diabetes Mellitus Patients

Bogdan Gabrys, Gregor Stiglic, Simon Kocbek, 2019, ICONIP.

Evolving Takagi-Sugeno-Kang Fuzzy Systems using Multi Population Grammar-Guided Genetic Programming

Athanasios Tsakonas, Bogdan Gabrys, B. Gabrys, 2016, IJCCI.

Fuzzy Base Predictor Outputs as Conditional Selectors for Evolved Combined Prediction System

Athanasios Tsakonas, Bogdan Gabrys, B. Gabrys, 2016, IJCCI.

Generalised bottom-up pruning: A model level combination of decision trees

Bogdan Gabrys, Mark Eastwood, B. Gabrys, 2012, Expert Syst. Appl..

Physical field models for pattern classification

Bogdan Gabrys, Dymitr Ruta, D. Ruta, 2003, Soft Comput..

Correntropy-based density-preserving data sampling as an alternative to standard cross-validation

Bogdan Gabrys, Marcin Budka, B. Gabrys, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

A framework for machine learning based on dynamic physical fields

Bogdan Gabrys, Dymitr Ruta, D. Ruta, 2009, Natural Computing.

Electrostatic Field Classifier for Deficient Data

Bogdan Gabrys, Marcin Budka, B. Gabrys, 2009, Computer Recognition Systems 3.

Accelerated learning algorithms of general fuzzy min-max neural network using a novel hyperbox selection rule

Bogdan Gabrys, T. T. Khuat, Thanh Tung Khuat, 2020, Inf. Sci..

Automated Deep Learning: Neural Architecture Search Is Not the End

B. Gabrys, Katarzyna Musial, Xuanyi Dong, 2021, Found. Trends Mach. Learn..

Cross-domain Meta-learning for Time-series Forecasting

Bogdan Gabrys, Abbas Raza Ali, Marcin Budka, 2018, KES.

Combination of Multi Level Forecasts

Bogdan Gabrys, Silvia Riedel, B. Gabrys, 2007, J. VLSI Signal Process..

Dynamic combination of forecasts generated by diversification procedures applied to forecasting of airline cancellations

Bogdan Gabrys, Christiane Lemke, Silvia Riedel, 2009, 2009 IEEE Symposium on Computational Intelligence for Financial Engineering.

Heterogeneous Feature Representation for Digital Twin-Oriented Complex Networked Systems

B. Gabrys, Katarzyna Musial, Jiaqi Wen, 2023, ArXiv.

Digital Twin-Oriented Complex Networked Systems based on Heterogeneous node features and interaction rules

B. Gabrys, Katarzyna Musial, Jiaqi Wen, 2023, ArXiv.