| A review of uncertainty quantification in deep learning: Techniques, applications and challenges M Abdar, F Pourpanah, S Hussain, D Rezazadegan, L Liu, ... Information Fusion 76, 243-297, 2021 | 3389 | 2021 |
| T-REX: a web server for inferring, validating and visualizing phylogenetic trees and networks A Boc, AB Diallo, V Makarenkov Nucleic Acids Research 40 (W1), W573-W579., 2012 | 588 | 2012 |
| A new machine learning technique for an accurate diagnosis of coronary artery disease M Abdar, W Książek, UR Acharya, RS Tan, V Makarenkov, P Pławiak Computer methods and programs in biomedicine 179, 104992, 2019 | 414 | 2019 |
| Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning M Abdar, M Samami, SD Mahmoodabad, T Doan, B Mazoure, ... Computers in biology and medicine 135, 104418, 2021 | 259 | 2021 |
| T-REX: reconstructing and visualizing phylogenetic trees and reticulation networks V Makarenkov Bioinformatics 17 (7), 664-668, 2001 | 218 | 2001 |
| Nonlinear redundancy analysis and canonical correspondence analysis based on polynomial regression V Makarenkov, P Legendre Ecology 83 (4), 1146-1161, 2002 | 214 | 2002 |
| DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring P Pławiak, M Abdar, J Pławiak, V Makarenkov, UR Acharya Information sciences 516, 401-418, 2020 | 186 | 2020 |
| Optimal Variable Weighting for Ultrametric and Additive Trees and K-means Partitioning: Methods and Software V Makarenkov, P Legendre Journal of Classification 18 (2), 245-271, 2001 | 154 | 2001 |
| Reconstruction of biogeographic and evolutionary networks using reticulograms P Legendre, V Makarenkov Systematic Biology 51 (2), 199-216, 2002 | 153 | 2002 |
| CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer M Abdar, V Makarenkov Measurement 146, 557-570, 2019 | 149 | 2019 |
| UncertaintyFuseNet: Robust Uncertainty-aware Hierarchical Feature Fusion Model with Ensemble Monte Carlo Dropout for COVID-19 Detection M Abdar, S Salari, S Qahremani, HK Lam, F Karray, S Hussain, ... Information Fusion 90, 364-381, 2023 | 148 | 2023 |
| An efficient method for the detection and elimination of systematic error in high-throughput screening V Makarenkov, P Zentilli, D Kevorkov, A Gagarin, N Malo, R Nadon Bioinformatics 23 (13), 1648-1657, 2007 | 119 | 2007 |
| NE-nu-SVC: a new nested ensemble clinical decision support system for effective diagnosis of coronary artery disease M Abdar, UR Acharya, N Sarrafzadegan, V Makarenkov Ieee Access 7, 167605-167620, 2019 | 117 | 2019 |
| SimPlot++: a Python application for representing sequence similarity and detecting recombination S Samson, É Lord, V Makarenkov Bioinformatics 38 (11), 3118–3120, 2022 | 114 | 2022 |
| From a phylogenetic tree to a reticulated network V Makarenkov, P Legendre Journal of Computational Biology 11 (1), 195-212, 2004 | 113 | 2004 |
| A hybrid latent space data fusion method for multimodal emotion recognition S Nemati, R Rohani, ME Basiri, M Abdar, NY Yen, V Makarenkov IEEE Access 7, 172948-172964, 2019 | 110 | 2019 |
| Inferring and validating horizontal gene transfer events using bipartition dissimilarity A Boc, H Philippe, V Makarenkov Systematic biology 59 (2), 195-211, 2010 | 106 | 2010 |
| Phylogenetic network construction approaches V Makarenkov, D Kevorkov, P Legendre Applied mycology and biotechnology 6, 61-97, 2006 | 105 | 2006 |
| A self-attention-based CNN-Bi-LSTM model for accurate state-of-charge estimation of lithium-ion batteries Z Sherkatghanad, A Ghazanfari, V Makarenkov Journal of Energy Storage 88, 111524, 2024 | 93 | 2024 |
| Using Traditional Machine Learning and Deep Learning Methods for On-and Off-Target Prediction in CRISPR/Cas9: A Review Z Sherkatghanad, M Abdar, J Charlier, V Makarenkov Briefings in Bioinformatics, bbad131, 2023 | 86 | 2023 |
Moloud AbdarSenior Data Scientist, The University of Queensland, AustraliaVerified email at uq.edu.au
