[1] Deep importance sampling using Tensor-Trains with application to a priori and a posteriori rare event estimation. SIAM MDS22, San Diego, California, U.S., September 27 2022.
[2] Risk averse optimization with tensor decompositions. 25th International Symposium on Mathematical Theory of Networks and Systems, Bayreuth, Germany, September 16 2022.
[3] Deep composition of Tensor-Trains using squared inverse Rosenblatt transports. 3rd IMA Conference on Inverse Problems from Theory to Application, International Centre for Mathematical Sciences, Edinburgh, UK, May 03 2022.
[4] Deep Tensor Train approximation for rare event simulation. SIAM UQ22, Atlanta, Georgia, U.S., April 13 2022.
[5] Deep Tensor Train approximations of high-dimensional functions. British Early Career Mathematicians’ Colloquium, University of Birmingham, UK, July 14 2021.
[6] A spectral tensor decomposition algorithm for time-dependent PDEs in Bayesian filtering. International Conference on Spectral and High Order Methods, Vienna, Austria, July 16 2021.
[7] Tensor decompositions for high-dimensional Hamilton-Jacobi-Bellman equations. SIAM OP21, ONLINE, July 23 2021.
[8] Deep composition of Tensor Trains using squared inverse Rosenblatt transports. SIAM CSE21, ONLINE, March 05 2021.
[9] Parallel time-dependent variational principle algorithm for Matrix Product States. Online Minisymposium on Low-rank Geometry and Computation, Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany, July 22 2020.
[10] Guaranteed a posteriori error bounds for low rank tensor approximate solutions. 8th Workshop on Matrix Equations and Tensor Techniques, Max Planck Institute Magdeburg, Germany, November 6 2019.
[11] A tensor decomposition approach for high-dimensional Hamilton-Jacobi-Bellman equations. Workshop 5 “Feedback Control” within the Special Semester on Optimization, Johann Radon Institute (RICAM), Linz, Austria, November 29 2019.
[12] Low-rank tensor decompositions for sampling of high-dimensional probability distributions. The 5th International Conference on Matrix Methods in Mathematics and applications, Institute of Numerical Mathematics, Moscow, August 19 2019.
[13] Parallel cross interpolation for high-precision calculation of high-dimensional integrals. 8th HPC Symposium, University of Bath, UK, June 6 2019.
[14] Tensor product solution to hamilton-jacobi-bellman equations for pdes. Group workshop at Ringberg, MPI Magdeburg, Germany, May 8 2019.
[15] Low-rank tensor decompositions for monte carlo sampling. 90th GAMM Annual Meeting, University of Vienna, Austria, February 21 2019.
[16] Solving large odes with conservation laws by low rank decompositions. Applications of Mathematics 2018, Institute of Mathematics, Prague, Czech Republic, August 23 2018.
[17] Approximation and sampling of multivariate probability distributions by tensor decompositions. SIAM Annual Meeting, Portland, USA, July 10 2018.
[18] Solving large odes with conservation laws by low rank decompositions. Numerical Analysis of Complex PDE Models in the Sciences, Erwin Schroedinger Institute, Vienna, Austria, June 12 2018.
[19] Low-rank tensor approximation and sampling of multivariate probability densities. BUC13 workshop, CIMAT, Guanajuato, Mexica, May 29 2018.
[20] Low-rank cross approximation algorithms for the solution of stochastic pdes. Reducing dimensions and cost for UQ in complex systems, Cambridge, United Kingdom, March 07 2018.
[21] Low rank tensor product surrogates for sampling from high dimensional distributions. Bath-RAL day, Rutherford Appleton Laboratory, Didcot, United Kingdom, January 22 2018.
[22] Tensor Train algorithms for stochastic PDE problems. Workshop on approximating high dimensional functions, The Alan Turing Institute, London, United Kingdom, December 18 2017.
[23] Low-rank tensor decomposition and cross approximation algorithms for parametric PDEs. ENUMATH Conference, Voss, Norway, September 26 2017.
[24] Low-rank tensor surrogates for sampling of high-dimensional distributions. SciCADE Conference, University of Bath, United Kingdom, September 15 2017.
[25] Low-rank cross approximation approach for reducing stochastic collocation models. Model Order Reduction Workshop, University of Durham, United Kingdom, August 12 2017.
[26] Low-rank solution of the optimal control problem for random Navier-Stokes equations. Numerical analysis conference, University of Strathclyde, United Kingdom, June 29 2017.
[27] Adaptive spectral time integration of ODEs in the Tensor Train decomposition. Scaling Cascades in Complex Systems, Freie University Berlin, Germany, March 27, 2017.
[28] A combination of Alternating Least Squares and low-rank cross approximation for solution of parametric PDEs. 5th BUC workshop on uncertainty quantification, University of Bath, UK, September 20, 2016.
[29] A combination of Alternating Least Squares and low-rank cross approximation for solution of parametric PDEs. 7th conference on Computational Methods in Applied Mathematics, University of Jyvaskyla, Finnland, August 01, 2016.
[30] Tensor product decompositions for high-dimensional problems in quantum chemistry. Theoretical Chemistry Seminar, University of Heidelberg, July 19, 2016.
[31] A tuning-free Schur complement preconditioner for linear systems arising from pde-constrained optimization. Conference of International Linear Algebra Society, University of Leuven, Belgium, July 11, 2016.
[32] A combination of Alternating Least Squares and low-rank cross approximation for solution of parametric PDEs. Workshop Computational Methods for High-Dimensional Problems, Ringberg Castle, Tegernsee, Germany, May 04, 2016.
[33] Alternating iteration for low-rank solution of the inverse stochastic Stokes equations. SIAM Conference on Uncertainty Quantification, EPFL, Lausanne, Switzerland, April 07, 2016.
[34] Tensor product approach for solution of multidimensional differential equations. Numerical Analysis Seminar, University of Bath, UK, March 11, 2016.
[35] Tensor product approach for solution of multidimensional differential equations. Mathematics Colloquium, University of Kent, UK, March 22, 2016.
[36] Tensor product approach for solution of multidimensional differential equations. Optimisation and Numerical Analysis Seminar, University of Birmingham, UK, February 25, 2016.
[37] Tensor product approach for solution of multidimensional differential equations. Computational Mathematics and Applications Seminar, University of Oxford, UK, February 11, 2016.
[38] Tensor product approach for solution of multidimensional differential equations. Applied Mathematics Seminar, University of Warwick, UK, February 05, 2016.
[39] Low-rank cross algorithms for approximations in parametric equations. SIAM conference on Applied Linear Algebra, Atlanta, US, October 28, 2015.
[40] Alternating iteration for low-rank solution of linear systems with large indefinite matrices. 5th Workshop Matrix Equations and Tensor Techniques, University of Bologna, Italy, September 21, 2015.
[41] Low-rank solution of optimization problems constrained by fractional differential equations. Conference European Numerical Mathematics and Advanced Applications, ODTU, Ankara, Turkey, September 14, 2015.
[42] On parallelization of alternating linear schemes for low-rank high-dimensional optimization. Conference Matrix Methods in Mathematics and Applications, Skoltech, Moscow, Russia, August 24, 2015.
[43] Low-rank solution of optimization problems constrained by fractional differential equations. Young Investigators Conference, RWTH, Aachen, Germany, July 22, 2015.
[44] Alternating iteration for low-rank solution of high-dimensional equations. Workshop Low-rank Optimization and Applications, HIM, Bonn, Germany, June 9, 2015.
[45] Solution of the chemical master equation by the separation of variables and alternating optimization methods. 6th Conference on Computational Methods in Applied Mathematics, Strobl, Austria, October 02, 2014.
[46] Solution of the chemical master equation by the separation of variables and alternating optimization methods. European Conference on Mathematical and Theoretical Biology, Gothenburg, June 16, 2014.
[47] Alternating minimal energy methods for linear systems in higher dimensions. Part II: Faster algorithm and application to nonsymmetric systems. ENUMATH Conference, EPFL Lausanne, August 26-30, 2013.
[48] Alternating minimal energy methods for linear systems in higher dimensions. Part II: Faster algorithm and application to nonsymmetric systems. MAFELAP, Brunel University, London, June 11, 2013.
[49] Fast adaptive alternating linear schemes in higher dimensions. Part 2: eigenproblems. NASCA Conference, University of Calais, June 24, 2013.
[50] Fast adaptive tensor product approach to eigenvalue problems in higher dimensions. Seminar of the Department of Chemistry, University of Southampton, June 27, 2013.
[51] Alternating minimal energy methods for linear systems in higher dimensions. Part II: Faster algorithm and application to nonsymmetric systems. Swiss numerics colloquium, EPFL, Lausanne, April 05, 2013.
[52] Fast adaptive alternating linear solvers. Implementation hints and application to Fokker-Planck and master equations. Workshop on algorithms for high-dimensional problems in quantum chemistry, University Southampton, February 26, 2013.
[53] Alternating minimal residual methods for linear systems in higher dimensions. Part II: heuristics and experiments. 29 GAMM Seminar on Uncertainty Quantification, MPI MIS, Leipzig, January 22, 2013.
[54] Advanced tensor representation and solution techniques with application to Fokker-Planck and master equations. CMAM-5, Humbolt University, Berlin, August 16–18, 2012.
[55] Advantages and difficulties of use of tensor methods in solution to the Fokker-Planck equation. 28 GAMM Seminar on Analysis and Numerical Methods in Higher Dimensions, MPI MIS, Leipzig, January 16–18, 2012.
[56] A gray-box DMRG algorithm for tensor structured solution to linear systems. 17th Conference of the International Linear Algebra Society, University Braunschweig, August 26, 2011.
[57] On a solution to a parabolic equation in the QTT format using the DMRG approach. 4th Workshop on High-Dimensional Approximation, University Bonn, June 27, 2011.
[58] Use of the DMRG scheme for structured linear system solution. 3rd International Conference on Matrix Methods in Mathematics and Applications, INM RAS, Moscow, June 24, 2011.
[59] Linear solvers in TT formats. 27th GAMM-Seminar on Approximation of Multiparametric functions, MPI MIS, Leipzig, January 26–28, 2011.
[60] Tensor-structured preconditioning for elliptic problems. Trilateral workshop on Separation of Variables and Applications, Nice, September 7–10, 2010.
[61] Tensor approximations for elliptic PDEs with jumping coefficients. Working Seminar on Joint German-Russian DFG-RFBR project, MPI MIS, Leipzig, May 2010.
[62] Tensor structure of solutions to elliptic problems with jumping coefficients. 26th GAMM-Seminar on Tensor Approximations and High-Dimensional Problems, MPI MIS, Leipzig, January 26–28, 2010.