| The docking of synaptic vesicles on the presynaptic membrane induced by α-synuclein is modulated by lipid composition WK Man, B Tahirbegi, MD Vrettas, S Preet, L Ying, M Vendruscolo, ... Nature Communication 12 (927), 2021 | 76 | 2021 |
| Variational mean-field algorithm for efficient inference in large systems of stochastic differential equations MD Vrettas, M Opper, D Cornford Physical Review E 91 (1), 012148, 2015 | 38 | 2015 |
| Estimating parameters in stochastic systems: A variational Bayesian approach MD Vrettas, D Cornford, M Opper Physica D: Nonlinear Phenomena 240 (23), 1877-1900, 2011 | 29 | 2011 |
| Toward a new parameterization of hydraulic conductivity in climate models: Simulation of rapid groundwater fluctuations in Northern California MD Vrettas, IY Fung Journal of Advances in Modeling Earth Systems, 2015 | 19 | 2015 |
| Quantifying simulator discrepancy in discrete-time dynamical simulators RD Wilkinson, MD Vrettas, D Cornford, JE Oakley Journal of agricultural, biological, and environmental statistics 16 (4 …, 2011 | 18 | 2011 |
| Sensitivity of transpiration to subsurface properties: Exploration with a 1‐D model MD Vrettas, IY Fung Journal of Advances in Modeling Earth Systems 9 (2), 1030-1045, 2017 | 17 | 2017 |
| Derivations of Variational Gaussian Process Approximation framework MD Vrettas, Y Shen, D Cornford Aston University, 2008 | 9 | 2008 |
| A new variational radial basis function approximation for inference in multivariate diffusions MD Vrettas, D Cornford, M Opper, Y Shen Neurocomputing 73 (7-9), 1186-1198, 2010 | 8 | 2010 |
| A variational radial basis function approximation for diffusion processes MD Vrettas, D Cornford, Y Shen 17th European Symposium on Artificial Neural Networks: Advances in …, 2009 | 5 | 2009 |
| Enhancing biomolecular simulations with hybrid potentials incorporating NMR data G Qi, MD Vrettas, C Biancaniello, M Sanz-Hernandez, CT Cafolla, ... Journal of Chemical Theory and Computation 18 (12), 7733-7750, 2022 | 4 | 2022 |
| Thermal Tuning of Protein Hydration in a Hyperthermophilic Enzyme G Fusco, C Biancaniello, MD Vrettas, A De Simone Frontiers in Molecular Biosciences, 1298, 2022 | 3 | 2022 |
| MetalHawk: Enhanced Classification of Metal Coordination Geometries by Artificial Neural Networks G Sgueglia, MD Vrettas, M Chino, A De Simone, A Lombardi Journal of chemical information and modeling, 2023 | 2 | 2023 |
| Approximate Bayesian techniques for inference in stochastic dynamical systems MD Vrettas Aston University, 2010 | 2 | 2010 |
| Classification of metal site coordination number and geometry through artificial neural networks G Sgueglia, M Vrettas, M Chino, A DE SIMONE, A Lombardi Book of Abstracts MYCS 2022, 48, 2021 | | 2021 |
| Application of a new hydraulic conductivity model to simulate rapid groundwater fluctuations in the Eel River watershed in Northern California MD Vrettas, IY Fung AGU Fall Meeting Abstracts 2015, GC23A-1126, 2015 | | 2015 |
| A new stochastic hydraulic conductivity approach for modeling one-dimensional vertical flow in variably saturated porous media. MD Vrettas, IY Fung AGU Fall Meeting Abstracts 2014, H43B-0964, 2014 | | 2014 |
| A Stochastic Hydraulic Conductivity Model for Weathered Bedrock. MD Vrettas, I Fung University of California at Berkeley, 2014 | | 2014 |
| Efficient Mean Field Variational Algorithm for Data Assimilation MD Vrettas, D Cornford, M Opper AGU Fall Meeting Abstracts 2013, H33J-01, 2013 | | 2013 |
| Remote Sensing Classification Uncertainty: Validating Probabilistic Pixel Level Classification M Vrettas, D Cornford, L Bastin, X Pons, E Sevillano, G Moré, P Serra, ... EGU General Assembly Conference Abstracts, EGU2013-11943, 2013 | | 2013 |
| Mean Field Variational Bayesian Data Assimilation M Vrettas, D Cornford, M Opper EGU General Assembly Conference Abstracts, 6464, 2012 | | 2012 |
Dan CornfordAston UniversityVerified email at aston.ac.uk
