| Physically consistent and efficient variational denoising of image fluid flow estimates A Vlasenko, C Schnorr IEEE transactions on image processing 19 (3), 586-595, 2009 | 17 | 2009 |
| Simulation of chemical transport model estimates by means of a neural network using meteorological data A Vlasenko, V Matthias, U Callies Atmospheric Environment 254, 118236, 2021 | 13 | 2021 |
| A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements A Vlasenko, ECC Steele, WAM Nimmo-Smith Measurement Science and Technology 26 (6), 065301, 2015 | 12 | 2015 |
| A pilot climate sensitivity study using the CEN coupled adjoint model (CESAM) D Stammer, A Köhl, A Vlasenko, I Matei, F Lunkeit, S Schubert Journal of Climate 31 (5), 2031-2056, 2018 | 11 | 2018 |
| The efficiency of geophysical adjoint codes generated by automatic differentiation tools AV Vlasenko, A Köhl, D Stammer Computer Physics Communications 199, 22-28, 2016 | 8 | 2016 |
| Variational approaches to image fluid flow estimation with physical priors A Vlasenko, C Schnörr Imaging Measurement Methods for Flow Analysis: Results of the DFG Priority …, 2009 | 8 | 2009 |
| Estimation of data assimilation error: A shallow-water model study A Vlasenko, P Korn, J Riehme, U Naumann Monthly Weather Review 142 (7), 2502-2520, 2014 | 6 | 2014 |
| Physically consistent variational denoising of image fluid flow estimates A Vlasenko, C Schnörr Joint Pattern Recognition Symposium, 406-415, 2008 | 6 | 2008 |
| Direct measurement of hairpin‐like vortices in the bottom boundary layer of the coastal ocean ECC Steele, WAM Nimmo‐Smith, A Vlasenko Geophysical Research Letters 43 (3), 1175-1183, 2016 | 4 | 2016 |
| Superresolution and denoising of 3d fluid flow estimates A Vlasenko, C Schnörr Joint Pattern Recognition Symposium, 482-491, 2009 | 4 | 2009 |
| Seasonal prediction of northern European winter air temperatures from SST anomalies based on sensitivity estimates A Köhl, A Vlasenko Geophysical Research Letters 46 (11), 6109-6117, 2019 | 3 | 2019 |
| Physics-based fluid flow restoration method A Vlasenko | 2 | 2010 |
| Examination of turbulence structures in the bottom boundary layer of the coastal ocean by submersible 3D-PTV E Steele, A Nimmo-Smith, A Vlasenko, P Hosegood | 1 | 2013 |
| Seasonal variability of trace gas emission (CH4, CO2) and in situ process studies D Wagner, L Kutzbach, H Becker, A Vlasenko, E Pfeiffer Expeditions in Siberia in 1999, 28-36, 2000 | 1 | 2000 |
| Data Analysis and Exploration with Computational Approaches V Wichert, LM Bouwer, N Abraham, H Brix, U Callies, E González Ávalos, ... Integrating Data Science and Earth Science: Challenges and Solutions, 29-53, 2022 | | 2022 |
| Estimation of NO2 and SO2 concentration changes in Europe from meteorological data with Neural Network A Vlasenko, V Mattias, U Callies EGU General Assembly Conference Abstracts, 1635, 2020 | | 2020 |
| Estimation of 4D-var Data Assimilation Error for Coupled Climate Models A Vlasenko, A Koehl, D Stammer EGU General Assembly Conference Abstracts, 16744, 2017 | | 2017 |
| Corrigendum: A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements (2015 Meas. Sci. Technol. 26 065301) A Vlasenko, ECC Steele, A Nimmo-Smith IOP Publishing, 2016 | | 2016 |
| A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements WAM Nimmo-Smith, A Vlasenko, ECC Steele | | 2015 |
| Intercomparison of adjoint codes generated by OpenAD, NAG AD and TAF automatic algorithmic differentiation tools AV Vlasenko, A Köhl, D Stammer XXX, 2015 | | 2015 |
W Alex M Nimmo-SmithAssociate Professor in Marine Physics, University of PlymouthVerified email at plymouth.ac.uk
