Publications list

• G. Fusco, C. Biancaniello, M. D. Vrettas and A. De Simone. "Thermal Tuning of Protein Hydration in an Hyperthermophilic Enzyme". Frontiers in Molecular Biosciences - Biological Modeling and Simulation, vol. 9, DOI: 10.3389/fmolb.2022.1037445, 2022.
  
• G. Qi, M. D. Vrettas, C. Biancaniello, M. Sanz-Hernandez, C. T. Cafolla, J. W. R. Morgan, Y. Wang, A. De Simone and D. J. Wales. "Enhancing Biomolecular Simulations With Hybrid Potentials Incorporating NMR Data". Journal of Chemical Theory and Computation, DOI: 10.1021/acs.jctc.2c00657, 2022.
• W. K. Man, B. Tahirbegi, M. D. Vrettas, S. Preet, L. Ying, M. Vendruscolo, A. De Simone and G. Fusco. "The docking of synaptic vesicles on the presynaptic membrane induced by α-synuclein is modulated by lipid composition". Nature Communications  12 (927), DOI:10.1038/s41467-021-21927-4, 2021.
• M. D. Vrettas and I. Fung. "Sensitivity of transpiration to subsurface properties: Exploration with a 1-D model". Journal of Advances in Modeling Earth Systems, DOI: 10.1002/2016MS000901, 2017.
• M. D. Vrettas and I. Fung. "Toward a new parameterization of hydraulic conductivity in climate models: Simulation of rapid groundwater fluctuations in Northern California". Journal of Advances in Modeling Earth Systems, DOI: 10.1002/2015MS000516, 2015.
• M. D. Vrettas, M. Opper and D. Cornford. "Variational mean-field algorithm for efficient inference in large systems of stochastic differential equations". Physical Review E, vol. 91 (1), 012148, DOI: 10.1103/PhysRevE.91.012148, 2015.

• M. D. Vrettas, D. Cornford and M. Opper. “Estimating parameters in stochastic systems: A variational Bayesian approach”. Physica D: Non-linear phenomena, vol. 240 (23), pp.: 1877-1900, DOI: 10.1016/j.physd.2011.08.013, 2011.

• R. D. Wilkinson, M. D. Vrettas, D. Cornford and J. Oakley. “Quantifying Simulator Discrepancy in Discrete-Time Dynamical Simulator”. Journal of Agricultural, Biological and Environmental Statistics. vol. 16 (4), pp.: 554-570, DOI: 10.1007/s13253-011-0077-3, 2011. There is also some supplementary material available here.

• M. D. Vrettas, D. Cornford, M. Opper and Y. Shen. “A new variational basis function approximation for multivariate diffusions”. Neurocomputing, vol. 73 (7), pp.: 1186 - 1198, DOI: 10.1016/j.neucom.2009.11.026, 2010.

• M. D. Vrettas, D. Cornford and Y. Shen. “A variational basis function approximation for diffusion processes”. In conference proceedings, European Symposium on Artificial Neural Networks (ESANN) - Advances in Computational Intelligence and Learning, pp.: 497-502, 2009.
• M. D. Vrettas and I. Fung. "Application of a new hydraulic conductivity model to simulate rapid ground water fluctuations in the Eel River watershed in Northern California". Abstract No. GC23A-1126, presented at the 2015 AGU Fall Meeting, December 2015.
• M. D. Vrettas and I. Fung. "A new stochastic hydraulic conductivity approach for modeling one-dimensional vertical flow in variably saturated porous media". Abstract No. H43B-0964, presented at the 2014 AGU Fall Meeting, December 2014.
• M. D. Vrettas, M. Opper and D. Cornford. "Efficient Mean Field Variational Algorithm for Data Assimilation (Invited)". Abstract No. H33J-01, presented at the 2013 AGU Fall Meeting, December 2013. (talk is available here)

• M. D. Vrettas, D. Cornford, L. Bastin, X. Pons, E. Sevillano, G. More, P. Serra and M. Ninyerola. "Remote Sensing Classification Uncertainty: Validating Probabilistic Pixel Level Classification". Vol. 15, EGU2013-11943, presented at the EGU General Assembly, April 2013.

• M. D. Vrettas, D. Cornford and M. Opper. “Mean Field Variational Bayesian Data Assimilation”. Vol. 14, EGU2012-6464, presented at the EGU General Assembly, April 2012.

• D. Cornford, Y. Shen, M. D. Vrettas and M. Opper. “Beyond weak constraint 4DVAR: a bridge to Monte Carlo methods?”. Vol. 12, EGU2010-9144, presented at the EGU General Assembly, April 2010.

• M. D. Vrettas, D. Cornford, M. Opper and Y. Shen. “Constrained variational Bayesian approximation for parameter estimation in diffusion processes”. Presented at the Bayesian Inference for Stochastic Processes (BISP) Workshop, June 2009.

• P. Adamidis, M. D. Vrettas and S. Kazarlis. “Exam timetabling with parallel evolutionary algorithms: comparison of different selection methods”. Presented at the 22nd European Conference on Operational Research (EURO XXII), July 2007.

Technical reports

• M. D. Vrettas and I. Fung. “A stochastic hydraulicc conductivity model for weathered bedrock”. Technical Report No. (EPS/2014/000), Department of Earth & Planetary Science, University of California - Berkeley, Berkeley CA 94720, December 2014.
  
• M. D. Vrettas, Y. Shen and D. Cornford. “Derivations of Variational Gaussian Process Approximation”. Technical Report No. (NCRG/2008/002), Neural Computing Research Group (NCRG) Aston University, Birmingham UK, B4 7ET, March 2008.

Thesis

• Ph.D. : "Approximate Bayesian techniques for inference in stochastic dynamical systems". Aston University, School of Engineering and Applied Science, UK, September 2010.
  
• B.Sc. : "Αυτοματοποιημένη δημιουργία προγραμμάτων εξεταστικής περιόδου. Βελτιστοποίηση με εφαρμογη παράλληλων εξελικτικών αλγορίθμων [in Greek]." (Automated creation of exam timetables. Optimization with application of parallel evolutionary algorithms). A.T.E.I. - Thessaloniki, Department of Information Engineering, Greece, 2004.
  

Posters

• G. Qi, M. D. Vrettas, C. Biancaniello, M. Sanz-Hernandez, C. T. Cafolla, J. W. R. Morgan, Y. Wang, A. De Simone and D. J. Wales. "Enhancing Biomolecular Simulations With Hybrid Potentials Incorporating NMR Data". BITS - Verona Italy, June 2022.
  
• M. D. Vrettas and I. Fung. "Application of a new hydraulic conductivity model to simulate rapid ground water fluctuations in the Eel River Watershed in Northern California". AGU - Fall Meetings, San Francisco CA, December 2015.
• M. D. Vrettas and I. Fung. "A new stochastic hydraulic conductivity approach for modeling one-dimensional vertical flow in variably saturated porous media". AGU - Fall Meetings, San Francisco CA, December 2014.
• M. D. Vrettas and I. Fung. "Towards Parameterization of Root-Rock Interaction for the CESM: I. Stochastic Hydraulic Conductivity". JCSDA Review & Science Meeting, College Park MD, 21-23 May 2014.
• M. D. Vrettas and I. Fung. "Assimilating subsurface hydrology data". Mathematics and Climate Research Network - Annual Meeting, 10-11 Oct, Chapel Hill, NC, 2013.
• M. D. Vrettas, et. al. "Uncertainty in Remote Sensing: Validating Probabilistic Pixel Level Classification". European Geophysical Union - Conference, Vienna - Austria April 2013.
• M. D. Vrettas, D. Cornford and Y. Shen. "Parameter Estimation of Dynamical Systems Driven by Noise". ESA - Summer School, Frascatti - Italy, 4-14 August 2008.

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