Motif-Based Classification of Time Series with Bayesian Networks and SVMs. - Krisztián Búza; Lars Schmidt-Thieme (GfKl, 2008)

Folksonomy-Based Collabulary Learning. - Leandro Balby Marinho; Krisztián Búza; Lars Schmidt-Thieme (ISWC, 2008)

Time-Series Classification Based on Individualised Error Prediction. - Krisztián Búza; Alexandros Nanopoulos; Lars Schmidt-Thieme (CSE, 2010)

Individualized Error Estimation for Classification and Regression Models. - Krisztián Búza; Alexandros Nanopoulos; Lars Schmidt-Thieme (GfKl, 2010)

Graph-Based Model-Selection Framework for Large Ensembles. - Krisztián Búza; Alexandros Nanopoulos; Lars Schmidt-Thieme (HAIS (1), 2010)

IQ estimation for accurate time-series classification. - Krisztián Búza; Alexandros Nanopoulos; Lars Schmidt-Thieme (CIDM, 2011)

Fusion of Similarity Measures for Time Series Classification. - Krisztián Búza; Alexandros Nanopoulos; Lars Schmidt-Thieme (HAIS (2), 2011)

Fast Classification of Electrocardiograph Signals via Instance Selection. - Krisztián Búza; Alexandros Nanopoulos; Lars Schmidt-Thieme; Júlia Koller (HISB, 2011)

A Distributed Genetic Algorithm for Graph-Based Clustering. - Krisztián Búza; Antal Buza; Piroska B. Kis (ICMMI, 2011)

Scalable Event-Based Clustering of Social Media Via Record Linkage Techniques. - Timo Reuter; Philipp Cimiano; Lucas Drumond; Krisztián Búza; Lars Schmidt-Thieme (ICWSM, 2011)

INSIGHT: Efficient and Effective Instance Selection for Time-Series Classification. - Krisztián Búza; Alexandros Nanopoulos; Lars Schmidt-Thieme (PAKDD (2), 2011)

Fusion Methods for Time-Series Classification. - Krisztian Antal Buza (2011)

Feedback Prediction for Blogs. - Krisztián Búza (GfKl, 2012)

SOHAC: Efficient Storage of Tick Data That Supports Search and Analysis. - Gábor I. Nagy; Krisztián Búza (ICDM, 2012)

GRAMOFON: General model-selection framework based on networks. - Krisztián Búza; Alexandros Nanopoulos; Tomás Horváth; Lars Schmidt-Thieme (Neurocomputing, 2012)

SUCCESS: A New Approach for Semi-supervised Classification of Time-Series. - Kristóf Marussy; Krisztián Búza (ICAISC (1), 2013)

Storage-optimizing clustering algorithms for high-dimensional tick data. - Krisztián Búza; Gábor I. Nagy; Alexandros Nanopoulos (Expert Syst. Appl., 2014)

BlogFeedback. - Krisztián Búza (UCI Machine Learning Repository, 2014)

Semi-supervised Naive Hubness Bayesian k-Nearest Neighbor for Gene Expression Data. - Krisztián Búza (CORES, 2015)

PROCESS: Projection-Based Classification of Electroencephalograph Signals. - Krisztián Búza; Júlia Koller; Kristóf Marussy (ICAISC, 2015)

Hubness-aware kNN classification of high-dimensional data in presence of label noise. - Nenad Tomasev; Krisztián Búza (Neurocomputing, 2015)

Nearest neighbor regression in the presence of bad hubs. - Krisztián Búza; Alexandros Nanopoulos; Gábor I. Nagy (Knowl. Based Syst., 2015)

Hubness-Aware Classification, Instance Selection and Feature Construction: Survey and Extensions to Time-Series. - Nenad Tomasev; Krisztián Búza; Kristóf Marussy; Piroska B. Kis (Feature Selection for Data and Pattern Recognition, 2015)

Person Identification Based on Keystroke Dynamics: Demo and Open Challenge. - Krisztián Búza (CAiSE Forum, 2016)

A Model for Classification Based on the Functional Connectivity Pattern Dynamics of the Brain. - Regina Meszlényi; Ladislav Peska; Viktor Gál; Zoltán Vidnyánszky; Krisztián Búza (ENIC, 2016)

Classification of fMRI data using dynamic time warping based functional connectivity analysis. - Regina Meszlényi; Ladislav Peska; Viktor Gál; Zoltán Vidnyánszky; Krisztián Búza (EUSIPCO, 2016)

Community Structure Detection for the Functional Connectivity Networks of the Brain. - Rodica Ioana Lung; Mihai Suciu 001; Regina Meszlényi; Krisztián Búza; Noémi Gaskó (PPSN, 2016)

Drug-target interaction prediction with hubness-aware machine learning. - Krisztián Búza (SACI, 2016)

How you type is who you are. - Krisztián Búza; Dóra Neubrandt (SACI, 2016)

ParkinsoNET: Estimation of UPDRS Score Using Hubness-Aware Feedforward Neural Networks. - Krisztián Búza; Noémi Ágnes Varga (Appl. Artif. Intell., 2016)

Classification of gene expression data: A hubness-aware semi-supervised approach. - Krisztián Búza (Comput. Methods Programs Biomed., 2016)

Correcting the hub occurrence prediction bias in many dimensions. - Nenad Tomasev; Krisztián Búza; Dunja Mladenic (Comput. Sci. Inf. Syst., 2016)

Towards Privacy-Aware Keyboards. - Krisztián Búza; Piroska B. Kis (CORES, 2017)

Projection-Based Person Identification. - Dóra Neubrandt; Krisztián Búza (CORES, 2017)

Using Echo State Networks for Cryptography. - Rajkumar Ramamurthy; Christian Bauckhage; Krisztián Búza; Stefan Wrobel (ICANN (2), 2017)

ALADIN: A New Approach for Drug-Target Interaction Prediction. - Krisztián Búza; Ladislav Peska (ECML/PKDD (2), 2017)

Drug-target interaction prediction: A Bayesian ranking approach. - Ladislav Peska; Krisztián Búza; Júlia Koller (Comput. Methods Programs Biomed., 2017)

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture. - Regina Meszlényi; Krisztián Búza; Zoltán Vidnyánszky (Frontiers Neuroinformatics, 2017)

Drug-target interaction prediction with Bipartite Local Models and hubness-aware regression. - Krisztián Búza; Ladislav Peska (Neurocomputing, 2017)

Time Series Classification and its Applications. - Krisztián Búza (WIMS, 2018)

Feature Selection with a Genetic Algorithm for Classification of Brain Imaging Data. - Annamária Szenkovits; Regina Meszlényi; Krisztián Búza; Noémi Gaskó; Rodica Ioana Lung; Mihai Suciu 001 (Advances in Feature Selection for Data and Pattern Recognition, 2018)

Factorization Machines for Blog Feedback Prediction. - Krisztián Búza; Tomás Horváth (CORES, 2019)

The Warping Window Size Effects the Accuracy of Person Identification based on Keystroke Dynamics. - Zakarya Farou; Krisztián Búza (ITAT, 2019)

Extreme Learning Machines with Regularization for the Classification of Gene Expression Data. - Dániel T. Várkonyi; Krisztián Búza (ITAT, 2019)

Encouraging an Appropriate Representation Simplifies Training of Neural Networks. - Krisztián Búza (CoRR, 2019)

Speeding up the SUCCESS Approach for Massive Industrial Datasets. - Krisztián Búza; Aleksandra Revina (INISTA, 2020)

ASTERICS: Projection-based Classification of EEG with Asymmetric Loss Linear Regression and Genetic Algorithm. - Krisztián Búza (SACI, 2020)

IT Ticket Classification: The Simpler, the Better. - Aleksandra Revina; Krisztián Búza; Vera G. Meister (IEEE Access, 2020)

Convolutional Neural Networks with Dynamic Convolution for Time Series Classification. - Krisztián Búza; Margit Antal (ICCCI (CCIS Volume), 2021)

SapiMouse: Mouse Dynamics-based User Authentication Using Deep Feature Learning. - Margit Antal; Norbert Fejér; Krisztián Búza (SACI, 2021)

medR: Software System for Managing Medical History and Patient Examination Data. - Anita-Bella Réthi; Krisztian Antal Buza; Orsolya Máthé; Mátyás Fosztó; Tamás Koncz; Károly Simon (SISY, 2021)

SapiAgent: A Bot Based on Deep Learning to Generate Human-Like Mouse Trajectories. - Margit Antal; Krisztián Búza; Norbert Fejér (IEEE Access, 2021)

Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering. - Bartosz Grabowski; Przemyslaw Glomb; Kamil Ksiazek; Krisztián Búza (ACIIDS (Companion), 2022)

Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation. - Kamil Ksiazek; Przemyslaw Glomb; Michal Romaszewski; Michal Cholewa; Bartosz Grabowski; Krisztián Búza (ICIAP (1), 2022)

Person Authentication using Visual Representations of Keyboard Typing Dynamics. - Ladislav Peska; Patrik Veselý; Tomás Skopal; Krisztián Búza (SNAMS, 2022)

Sparsity-Invariant Convolution for Forecasting Irregularly Sampled Time Series. - Krisztián Búza (ICCCI, 2023)

A Simple and Effective Classifier for the Detection of Schizophrenia and Bipolar Disorder based on Heart Rate Variability Time Series. - Krisztián Búza; Kamil Ksiazek; Wilhelm Masarczyk; Przemyslaw Glomb; Piotr Gorczyca; Magdalena Piegza (ITAT, 2023)

Advancements in Text Subjectivity Analysis: From Simple Approaches to BERT-Based Models and Generalization Assessments. - Margit Antal; Krisztián Búza; Szilárd Nemes (ICCCI (CCIS Volume 1), 2024)

ROCKET with Dynamic Convolution for Time Series Classification. - Krisztián Búza; Margit Antal (ICCCI (CCIS Volume 1), 2024)

Activity Recognition Based on Accelerometer Data with Enhanced ROCKET Algorithm. - Krisztián Búza (SACI, 2024)

Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data. - Kamil Ksiazek; Wilhelm Masarczyk; Przemyslaw Glomb; Michal Romaszewski; Iga Stoklosa; Piotr Scislo; Pawel Debski; Robert Pudlo; Krisztián Búza; Piotr Gorczyca; Magdalena Piegza (Comput. Biol. Medicine, 2024)

Conformal prediction for out-of-distribution time-series classification. - Alexandros Nanopoulos; Krisztián Búza (Appl. Intell., 2025)