| A variational approximation scheme for radial polyconvex elasticity that preserves the positivity of Jacobians A Miroshnikov, AE Tzavaras arXiv preprint arXiv:1408.0541, 2014 | 17 | 2014 |
| Wasserstein-based fairness interpretability framework for machine learning models A Miroshnikov, K Kotsiopoulos, R Franks, A Ravi Kannan Machine Learning 111 (9), 3307-3357, 2022 | 15 | 2022 |
| Parallel Markov chain Monte Carlo for non‐Gaussian posterior distributions A Miroshnikov, Z Wei, EM Conlon Stat 4 (1), 304-319, 2015 | 14 | 2015 |
| ParallelMCMCcombine: an R package for Bayesian methods for big data and analytics A Miroshnikov, EM Conlon PloS one 9 (9), e108425, 2014 | 14 | 2014 |
| Relative entropy in hyperbolic relaxation for balance laws A Miroshnikov, K Trivisa arXiv preprint arXiv:1408.0815, 2014 | 10 | 2014 |
| Mutual information-based group explainers with coalition structure for machine learning model explanations A Miroshnikov, K Kotsiopoulos, K Filom, AR Kannan arXiv preprint arXiv:2102.10878, 2021 | 8 | 2021 |
| Computing the joint distribution of the total tree length across loci in populations with variable size A Miroshnikov, M Steinrücken Theoretical population biology 118, 1-19, 2017 | 7 | 2017 |
| Convergence of variational approximation schemes for elastodynamics with polyconvex energy A Miroshnikov, AE Tzavaras Zeitschrift für Analysis und ihre Anwendungen 33 (1), 43-64, 2013 | 7 | 2013 |
| On the construction and properties of weak solutions describing dynamic cavitation A Miroshnikov, AE Tzavaras Journal of Elasticity 118, 141-185, 2015 | 6 | 2015 |
| parallelMCMCcombine: Methods for combining independent subset Markov chain Monte Carlo (MCMC) posterior samples to estimate a posterior density given the full data set A Miroshnikov, E Conlon R package version 1, 2014 | 6 | 2014 |
| System and method for mitigating bias in classification scores generated by machine learning models A Miroshnikov, K Kotsiopoulos, AR Kannan, R Kulkarni, S Dickerson US Patent App. 16/891,989, 2021 | 3 | 2021 |
| Model-agnostic bias mitigation methods with regressor distribution control for Wasserstein-based fairness metrics A Miroshnikov, K Kotsiopoulos, R Franks, AR Kannan arXiv preprint arXiv:2111.11259, 2021 | 3 | 2021 |
| Weak* solutions I: A new perspective on solutions to systems of conservation laws A Miroshnikov, R Young arXiv preprint arXiv:1511.02579, 2015 | 3 | 2015 |
| Motile Geobacter dechlorinators migrate into a model source zone of trichloroethene dense non-aqueous phase liquid: Experimental evaluation and modeling J Philips, A Miroshnikov, PJ Haest, D Springael, E Smolders Journal of contaminant hydrology 170, 28-38, 2014 | 3 | 2014 |
| On marginal feature attributions of tree-based models K Filom, A Miroshnikov, K Kotsiopoulos, AR Kannan arXiv preprint arXiv:2302.08434, 2023 | 2 | 2023 |
| Cellulose biodegradation models; an example of cooperative interactions in structured populations PE Jabin, A Miroshnikov, R Young ESAIM: Mathematical Modelling and Numerical Analysis 51 (6), 2289-2318, 2017 | 2 | 2017 |
| Weak* solutions II: The vacuum in Lagrangian gas dynamics A Miroshnikov, R Young SIAM Journal on Mathematical Analysis 49 (3), 1810-1843, 2017 | 2 | 2017 |
| Springer Link J Liang, KW Ng, G Tian, RE Gaunt, S Iyengar, ABO Daalhuis, B Simsek, ... | 2 | 2007 |
| Approximation of group explainers with coalition structure using Monte Carlo sampling on the product space of coalitions and features K Kotsiopoulos, A Miroshnikov, K Filom, AR Kannan arXiv preprint arXiv:2303.10216, 2023 | 1 | 2023 |
| Computing system and method for creating a data science model having reduced bias A Miroshnikov, K Kotsiopoulos, AR Kannan, R Kulkarni, S Dickerson, ... US Patent App. 17/900,753, 2022 | 1 | 2022 |
Athanasios TzavarasKing Abdullah University of Science and Technology (KAUST)Verified email at kaust.edu.sa
