Conditional-value-at-risk estimation via reduced-order models M Heinkenschloss, B Kramer, T Takhtaganov, K Willcox SIAM/ASA Journal on Uncertainty Quantification 6 (4), 1395-1423, 2018 | 30 | 2018 |
Adaptive reduced-order model construction for conditional value-at-risk estimation M Heinkenschloss, B Kramer, T Takhtaganov SIAM/ASA Journal on Uncertainty Quantification 8 (2), 668-692, 2020 | 22 | 2020 |
Cosmic Inference: Constraining Parameters with Observations and a Highly Limited Number of Simulations T Takhtaganov, Z Lukić, J Müller, D Morozov The Astrophysical Journal 906 (2), 74, 2021 | 15 | 2021 |
Adaptive Gaussian process surrogates for Bayesian inference T Takhtaganov, J Müller arXiv preprint arXiv:1809.10784, 2018 | 13 | 2018 |
Efficient estimation of coherent risk measures for risk-averse optimization problems governed by partial differential equations with random inputs T Takhtaganov | 3 | 2017 |
High-dimensional integration for optimization under uncertainty TA Takhtaganov Rice University, 2015 | 3 | 2015 |
OPTIMIZATION UNDER UNCERTAINTY FOR THE SHOCKLEY AND THE DRIFT-DIFFUSION MODELS OF A DIODE TA TAKHTAGANOV, DP KOURI, D RIDZAL, E KEITER CCR, 165, 2014 | 2 | 2014 |
AN IMPORTANCE SAMPLING APPROACH TO RISK ESTIMATION TA TAKHTAGANOV, DP KOURI, D RIDZAL CCR, 77, 2016 | 1 | 2016 |
Xyce HK Thomquist, DA Fixel, DB Fett, N Johnson, L Boucheron, DN Bames, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017 | | 2017 |
Electrochemical energy storage devices AA Hernandez, G Li, S Nguyen, F Smith, T Takhtaganov University of Minnesota. Institute for Mathematics and Its Applications, 2014 | | 2014 |