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 | 1863 | 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 | 531 | 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 | 307 | 2019 |
T-REX: reconstructing and visualizing phylogenetic trees and reticulation networks V Makarenkov Bioinformatics 17 (7), 664-668, 2001 | 211 | 2001 |
Nonlinear redundancy analysis and canonical correspondence analysis based on polynomial regression V Makarenkov, P Legendre Ecology 83 (4), 1146-1161, 2002 | 188 | 2002 |
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 | 172 | 2021 |
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 | 157 | 2001 |
Reconstruction of biogeographic and evolutionary networks using reticulograms P Legendre, V Makarenkov Systematic Biology 51 (2), 199-216, 2002 | 151 | 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 | 137 | 2020 |
CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer M Abdar, V Makarenkov Measurement 146, 557-570, 2019 | 128 | 2019 |
From a phylogenetic tree to a reticulated network V Makarenkov, P Legendre Journal of Computational Biology 11 (1), 195-212, 2004 | 118 | 2004 |
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 | 114 | 2007 |
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 | 112 | 2023 |
Phylogenetic network construction approaches V Makarenkov, D Kevorkov, P Legendre Applied mycology and biotechnology 6, 61-97, 2006 | 104 | 2006 |
Inferring and validating horizontal gene transfer events using bipartition dissimilarity A Boc, H Philippe, V Makarenkov Systematic biology 59 (2), 195-211, 2010 | 102 | 2010 |
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 | 91 | 2019 |
Statistical analysis of systematic errors in high-throughput screening D Kevorkov, V Makarenkov SLAS Discovery 10 (6), 557-567, 2005 | 79 | 2005 |
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 | 75 | 2019 |
An algorithm for the fitting of a tree metric according to a weighted least-squares criterion V Makarenkov, B Leclerc Journal of classification 16 (1), 3-26, 1999 | 74 | 1999 |
A weighted least-squares approach for inferring phylogenies from incomplete distance matrices V Makarenkov, FJ Lapointe Bioinformatics 20 (13), 2113-2121, 2004 | 71 | 2004 |