Alexander Litvinenko - Talks

 

Alexander Litvinenko  

 

​​        Research Themes    Projects    Teaching    Talks 

  Educational talk for 1st year students at University of Nottingham.
Litvinenko_Nottingham_determinant.pdfLitvinenko_Nottingham_determinant.pdf


 Talks

  1. Low-rank tensor methods for solving PDEs with uncertain coefficients, invited talk at University of Edinburgh, March 2017.
  2. Low-rank tensor methods for solving PDEs with uncertain coefficients, invited talk at University of Nottingham, March 2017.
  3. Likelihood approximation with hierarchical matrices for large spatial datasets, 7th Workshop on High-Dimensional Approximation, Sydney, Australia, Feb. 13-17, 2017.
  4. Tensor completion techniques in Data Assimilation, Bayesian Updata and UQ problems, SIAM CSE, Atlanta, Feb. 27, 2017.
  5. Low-rank tensor methods for PDEs with uncertain coefficients and Bayesian Update surrogate, UNSW, Sydney, Australia, February 2017
  6. Low-rank tensor methods for PDEs with uncertain coefficients and Bayesian Update surrogate, Colorado Denver, USA, January 2017
  7. Numerical methods for solving stochastic PDEs in Tensor Train data format, KU Leuven, Belgium, July 2016
  8. Approximation of non-linear Bayesian Update for inverse problems,  Inverse Problems & Modeling and Simulation Conference, Fethiye, Turkey, May 2016
  9. Non-linear approximation of Bayesian Update, ENKF Workshop, Norway, May 2016
  10. Hierarchical matrix techniques for maximum likelihood covariance estimation, The Third Scalable Hierarchical Algorithms for eXtreme Computing (SHAXC-3) workshop, King Abdullah University of Science and Technology, May 2016
  11. Hierarchical matrix techniques for maximum likelihood covariance estimation, SIAM UQ, Lausanne, April 2016
  12. Possible applications of low-rank tensors in statistics and UQ. Hausdorff School 2016: Low-rank Tensor Techniques in Numerical Analysis and Optimization, Bonn, Germany, April 2016
  13. Hierarchical matrix techniques for maximum likelihood covariance estimation, GAMM Conference, 7-11 March 2016, Braunschweig, Germany.
  14. Fast and cheap approximation of large covariance matrix with hierarchical matrix technique, UQAW Workshop, 5-11 Jan. 2016, KAUST.
  15. Uncertainty Quantification with applications, presentation for Veolia, 18. Dec. 2015, KAUST
  16. Low-rank tensor approximation of big data, Nov. 25, 2015, meeting with Aramco, KAUST
  17. Uncertainty quantification with applications , Nov. 17, 2015, meeting with Aramco, KAUST
  18. Introductory  talk in  Extreme Computing Research Center , Oct. 2015, KAUST. 
  19. Numerical methods for solving stochastic partial differential equations in the Tensor Train format . Aug. 18, 2015, Leipzig.
  20. Polynomial Chaos Expansion of random coefficients and the solution of stochastic partial differential equations in the Tensor Train format , Aug. 10-14, 2015, ICIAM in Beijing, China
  21. Efficient Analysis of High Dimensional Data in Tensor Formats , (joint work with M. Espig, W. Hackbusch,H. G. Matthies, E. Zander), Aug. 10-14, 2015, ICIAM in Beijing, China
  22. Talk Introduction into hierarchical matrix technique , July 2015, group "Computational Methods in Systems and Control Theory" of Prof. P. Benner, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
  23. Introduction to tensors: different formats, arithmetics, ranks, few examples , Goethe University Frankfurt, Germany , July 23, 2015.
  24. Sampling and low-ranktensor Approximation of the Response Surface , UMRIDA UQ Workshop, TU Delft, 15 April, 2015.
  25. Level sets, April 20-23, 2015, Aramco, Dhahran, Saudi Arabia
  26. Polynomial Chaos Expansion of random coefficients and the solution of stochastic partial differential equations in the Tensor Train format,       SIAM CSE, Salt Lake City, USA, 2015
  27. Response Surface in low-rank Tensor Train Format for Uncertainty Quantification, September 2014, University of Stuttgart, Germany
  28. Inverse Problems and Uncertainty Quantification , December 2014, Hong Kong, Conference IPOC2014.
  29. Response Surface in low-rank Tensor Train Format for Uncertainty Quantification, August 2014, WIAS Berlin, Germany
  30. Overview of numerical methods for Uncertainty Quantification, CS Graduate Seminar, KAUST, May 2014
  31. Application of Hierarchical matrices for domain decomposition, KAUST, SRI UQ, 2014
  32. AMCS Graduate Seminar: Scalable hierarchical algorithms for PDEs and UQ, KAUST, April 2014
  33. Uncertainty Quantification, Inverse Problems and application, KICP Meeting, KAUST, April 2014
  34. Uncertainty Quantification and Risk Management, Meeting with industry partner LaFarge Company , KAUST, April 2014
  35. Response Surface and its low-rank update for uncertainty quantification in reservoir modeling, Meeting with Aramco, April 2014
  36. Response Surface in low-rank Tensor Train Format for Uncertainty Quantification, May 2014, KAUST
  37. Short lecture course: Low rank tensor representation / examples, KAUST, 2013-2014
  38. AMCS Graduate Seminar: Scalable hierarchical algorithms for PDEs and UQ Alexander Litvinenko and Rio Yokota, KAUST, April 2014
  39. Response Surface in low-rank Tensor Train Format for Uncertainty Quantification, SHAXC, Workshop at KAUST, April 2014
  40. Implementation of Non-linear Bayesian Update of Random Variables , SIAM UQ Conference, USA, March 2014
  41. Uncertainty Quantification with application in geology, Meeting with Maaden, KAUST, October 2013
  42. MIS MPI Leipzig, Germany, 04.2013
  43. Efficient Analysis of High Dimensional Data in Tensor Formats, KAUST, 04.2013
  44. Non-sampling functional approximation of linear and non-linear Bayesian Update, GAMM Conference, Novi Sad, Serbia, 03.2013
  45. Non-sampling functional approximation of linear and non-linear Bayesian Update, SIAM CSE Conference, Boston, USA, 02.2013
  46. Data sparse approximation of the Karhunen-Loeve expansion, Oberwolfach Mini-Workshop: Numerical Upscaling for Media with Deterministic and Stochastic Heterogeneity, Germany, 02.2013
  47. Sampling and Low-Rank Tensor Approximations, Oberwolfach Workshop Numerical Methods for PDE Constrained Optimization with Uncertain Data, Germany, 01.2013
  48. Non-sampling functional approximation of linear and non-linear Bayesian Update, GAMM Seminar, MIS MPG Leipzig, Germany, 01.2013
  49. Sampling-free linear Bayesian update of polynomial chaos representations, Research Seminar on TU Braunschweig, 12.2012
  50. Efficient Uncertainty Quantification for the Complete Field Solution, MUNA Final Project meeting, DLR Braunschweig, Germany, 10.2012
  51. Tensor Approximation Methods for Parameter Identification, SIAM Conference on Applied Linear Algebra, Valencia, Spain, 06.2012
  52. Multi-linear algebra and different tensor formats with applications, Research Seminar Technische Universität Braunschweig, Germany, 05.2012
  53. Non-linear Bayesian Update, CODECS Project meeting, RWTH Aachen, Aachen, 05.2012
  54. Uncertainty Quantification in Numerical Aerodynamics, SIAM UQ Conference, Raleigh, NC, USA, 04.2012
  55. Efficient Analysis of High Dimensional Data in Tensor Formats, SIAM UQ Conference, Raleigh, NC, USA, 04.2012
  56. Uncertainty Quantification in numerical Aerodynamic via low-rank Response Surface, GAMM Conference, Darmstadt, Germany, 03.2012
  57. Efficient Analysis of High Dimensional Data in Tensor Formats, Workshop High-Order Numerical Approximation for Partial Differential Equations, Hausdorff Center for Mathematics, University of Bonn, Germany, 02.2012
  58. Efficient Analysis of High Dimensional Data in Tensor Formats, University of Trier, Germany, 02.2012
  59. Efficient Analysis of High Dimensional Data in Tensor Formats, GAMM Seminar Analysis and Numerical Methods in Higher Dimensions, Leipzig, 01.2012
  60. Bayesian Update in low-rank tensor format, Workshop on Matrix Equations and Tensor Techniques, Aachen, Germany, 22.11.2011
  61. Low-rank approximation and Bayesian update, University of Trier, 11.11.2011.
  62. Low-rank direct Bayesian update of polynomial chaos coefficients, GAMM Activity Group Applied and Numerical Linear Algebra Workshop, Bremen, Germany, 22.09.2011
  63. Bayesian Update in low-rank tensor format, Deutsch- französische Sommerschule Quantifizierung von Ungewissheiten in Mechanik und Werkstoffwissenschaften, Pforzheim, Germany, 24.08.2011
  64. Uncertainties Quantification and Data Compression in numerical Aerodynamics, GAMM conference, Graz, Austria, 19.04.2011
  65. Low-rank response surface with application in numerical aerodynamic, 1st International Symposium on Uncertainty Modelling in Engineering (ISUME), CVUT Prague, Czech Republic, 02.05.2011
  66. Low-rank approximation and Bayesian update, University of Stuttgart, Germany, 31.05.2011.
  67. Efficient Analysis of High Dimensional Data in Tensor Formats, Workshop on Sparse Grids, Hausdorff Research Institute for Mathematics, Bonn, Germany, 05.2011
  68. Uncertainties Quantification and Data Compression in numerical Aerodynamics, SIAM CSE conference, Reno, USA, 1.03.2011
  69. Low-rank data format for uncertainty quantification. SMTDA-2010 International Conference, Crete, Greece, 08.-11.06.2010
  70. Sparse data formats and efficient numerical methods for uncertainties quantification in numerical aerodynamics. IV European Congress on Computational Mechanics (ECCM IV): Solids, Structures and Coupled Problems in Engineering, Paris, France, 16.-21.05.2010
  71. Sparse data formats and efficient numerical methods for uncertainties quantification in numerical aerodynamics. Fourth International Workshop on the Numerical Analysis of Stochastic Partial Differential Equations, TU Bergakademie, Freiberg, Germany, 20.-21.09.2010
  72. Sparse data representation of random fields, GAMM 2009, Germany
  73. Numerical methods for quantification of uncertainties in stochastic aerodynamics, MUNA Workshop, DLR Braunschweig, Germany, 2009
  74. Quantification of uncertainties in the angle of attack and Mach number, MUNA Project meeting, RWTH Aachen, Germany, 2009
  75. Numerical methods for stochastic transport equation, SIAM Geosciences, Leipzig, Germany, 2009
  76. Application of sparse tensor techniques for solving stochastic transport equation , Inverse problems conference, Vienna, Austria, 2009
  77. Numerical methods for quantificauncertaintiesrtanties in stochastic aerodynamics, MUNA Project meeting, Braunschweig, 2009
  78. Comparison of Monte Carlo and sparse grids methods, Stuttgart, Germany 2009.
  79. Quantification of uncertainties in angle of attack and Mach number , NODESIM-CFD Workshop on Quantification of CFD UncertaintiesBrussel, Belgium, 2009.
  80. Data sparse approximation of the Karhunen-Loeve expansion, GAMM Meeting, MIS MPI Leipzig, Germany, 2008.
  81. Sparse techniques for information extraction in stochastic PDEs, Bonn, Germany, 2008
  82. Stochastic framework for turbulence modeling, MUNA Project meeting, RWTH Aachen, Germany, 2008
  83. Mathematical methods for quantification of uncertainties in stochastic Navier-Stokes Equation, DLR, Germany,2008
  84. Stochastic numerical methods, MUNA Project meeting, Uni Trier, Germany, 2008
  85. Numerical methods for quantification of uncertanties instochastic aerodynamics, MUNA Project meeting, Braunschweig, 2008
  86. Data sparse approximation of the Karhunen-Loeve expansion, Workshop at HU Berlin, organized by C. Carstensen, Germany, 2008


Posters:
  1. Likelihood Approximation with Hierarchical Matrices for Large Spatial Datasets, Workshop: Statistics for high-dimensional and Complex Data, Nov. 6-9, 2016, KAUST