| Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods G Suryanarayana, J Lago, D Geysen, P Aleksiejuk, C Johansson Energy 157, 141-149, 2018 | 161 | 2018 |
| Optimal flexibility dispatch problem using second-order cone relaxation of AC power flows SS Torbaghan, G Suryanarayana, H Höschle, R D'hulst, F Geth, C Caerts, ... IEEE Transactions on Power Systems 35 (1), 98-108, 2019 | 58 | 2019 |
| Multilevel Monte Carlo simulation for Lévy processes based on the Wiener–Hopf factorisation A Ferreiro-Castilla, AE Kyprianou, R Scheichl, G Suryanarayana Stochastic Processes and their Applications 124 (2), 985-1010, 2014 | 49 | 2014 |
| Tent-transformed lattice rules for integration and approximation of multivariate non-periodic functions R Cools, FY Kuo, D Nuyens, G Suryanarayana Journal of Complexity 36, 166-181, 2016 | 31 | 2016 |
| A data driven method for optimal sensor placement in multi-zone buildings G Suryanarayana, J Arroyo, L Helsen, J Lago Energy and Buildings 243, 110956, 2021 | 24 | 2021 |
| Optimal control strategies for seasonal thermal energy storage systems with market interaction J Lago, G Suryanarayana, E Sogancioglu, B De Schutter IEEE Transactions on Control Systems Technology 29 (5), 1891-1906, 2020 | 22 | 2020 |
| A market framework for grid balancing support through imbalances trading J Lago, K Poplavskaya, G Suryanarayana, B De Schutter Renewable and Sustainable Energy Reviews 137, 110467, 2021 | 17 | 2021 |
| Reconstruction and collocation of a class of non-periodic functions by sampling along tent-transformed rank-1 lattices G Suryanarayana, D Nuyens, R Cools Journal of Fourier Analysis and Applications 22, 187-214, 2016 | 15 | 2016 |
| Rank-1 lattice rules for multivariate integration in spaces of permutation-invariant functions: Error bounds and tractability D Nuyens, G Suryanarayana, M Weimar Advances in Computational Mathematics 42, 55-84, 2016 | 10 | 2016 |
| Building day-ahead bidding functions for seasonal storage systems: A reinforcement learning approach J Lago, E Sogancioglu, G Suryanarayana, F De Ridder, B De Schutter IFAC-PapersOnLine 52 (4), 488-493, 2019 | 7 | 2019 |
| Hierarchical implicit controller for shielded system in a grid D Vanhoudt, G Suryanarayana, F De Ridder, JC Johansson US Patent 10,983,484, 2021 | 5 | 2021 |
| Strang Splitting in Combination with Rank-1 and Rank-r Lattices for the Time-Dependent Schrödinger Equation Y Suzuki, G Suryanarayana, D Nuyens SIAM Journal on Scientific Computing 41 (6), B1254-B1283, 2019 | 5 | 2019 |
| Construction of quasi-Monte Carlo rules for multivariate integration in spaces of permutation-invariant functions D Nuyens, G Suryanarayana, M Weimar Constructive Approximation 45, 311-344, 2017 | 5 | 2017 |
| Approximation in cosine space using tent transformed lattice rules D Nuyens, G Suryanarayana, R Cools, FY Kuo 2014, Slides of talk given at ICERM Semester Program, 2014 | 3 | 2014 |
| Rank-1 lattices and Strang splitting for the time-dependent Schrödinger equation Y Suzuki, G SURYANARAYANA, D Nuyens Workshop on High-Dimensional Approximation (HDA2017), Date: 2017/02/13-2017 …, 2017 | 2 | 2017 |
| Advanced Quasi-Monte Carlo Algorithms for High-dimensional Integration and Approximation G Suryanarayana | 2 | 2016 |
| Integration of permutation invariant functions G Suryanarayana, D Nuyens, M Weimar International Conference on Monte Carlo and Quasi-Monte Carlo Methods in …, 2016 | 1 | 2016 |
| Quasi Monte-Carlo methods for the TDSE (Time dependent Schrödinger equation) G Suryanarayana, D Nuyens, R Cools IAP DYSCO Study Day: Dynamical systems, control and optimization, Date: 2015 …, 2015 | 1 | 2015 |
| Approximation with lattice points D Nuyens, G Suryanarayana, R Cools, FY Kuo Dagstuhl Seminar on Algorithms and Complexity for Continuous Problems, Date …, 2015 | 1 | 2015 |
| On lattice rules, approximation and Lebesgue constants R Cools, D Nuyens, G Suryanarayana Dagstuhl Seminar on Algorithms and Complexity for Continuous Problems, Date …, 2015 | 1 | 2015 |
Jesus LagoAmazonBestätigte E-Mail-Adresse bei amazon.com
