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ORCIDThemistoklis P. Sapsis
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2020 – today
- 2024
[i23]Benedikt Barthel Sorensen, Alexis-Tzianni Charalampopoulos, Shixuan Zhang, Bryce Harrop, Ruby Leung, Themistoklis P. Sapsis:
A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics. CoRR abs/2402.18484 (2024)- [i22]Eirini Katsidoniotaki, Biao Su, Eleni Kelasidi, Themistoklis P. Sapsis:
Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages. CoRR abs/2406.04519 (2024) - [i21]Yorgos M. Psarellis, Themistoklis P. Sapsis, Ioannis G. Kevrekidis:
Active search for Bifurcations. CoRR abs/2406.11141 (2024) - [i20]Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez, Zhong Yi Wan, Rob Carver, Fei Sha, Themistoklis P. Sapsis:
A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data. CoRR abs/2408.02688 (2024) - 2023
- [j19]Jiaqi Zhang
, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler:
Active learning for optimal intervention design in causal models. Nat. Mac. Intell. 5(10): 1066-1075 (2023) - [i19]Stephen Guth, Alireza Mojahed, Themistoklis P. Sapsis:
Evaluation of machine learning architectures on the quantification of epistemic and aleatoric uncertainties in complex dynamical systems. CoRR abs/2306.15159 (2023) - 2022
- [j18]Hassan Arbabi, Themistoklis P. Sapsis:
Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics. SIAM/ASA J. Uncertain. Quantification 10(2): 555-583 (2022) - [j17]Ethan Pickering, Stephen Guth, George Em Karniadakis, Themistoklis P. Sapsis:
Discovering and forecasting extreme events via active learning in neural operators. Nat. Comput. Sci. 2(12): 823-833 (2022) - [i18]Ethan Pickering, Themistoklis P. Sapsis:
Structure and Distribution Metric for Quantifying the Quality of Uncertainty: Assessing Gaussian Processes, Deep Neural Nets, and Deep Neural Operators for Regression. CoRR abs/2203.04515 (2022) - [i17]Ethan Pickering, George Em Karniadakis, Themistoklis P. Sapsis:
Discovering and forecasting extreme events via active learning in neural operators. CoRR abs/2204.02488 (2022) - [i16]Ethan Pickering, Themistoklis P. Sapsis:
Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models. CoRR abs/2208.13080 (2022) - [i15]Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler:
Active Learning for Optimal Intervention Design in Causal Models. CoRR abs/2209.04744 (2022) - [i14]Antoine Blanchard, Nishant Parashar, Boyko A. Dodov, Christian Lessig, Themistoklis P. Sapsis:
A Multi-Scale Deep Learning Framework for Projecting Weather Extremes. CoRR abs/2210.12137 (2022) - 2021
- [j16]Antoine Blanchard, Themistoklis P. Sapsis:
Bayesian optimization with output-weighted optimal sampling. J. Comput. Phys. 425: 109901 (2021) - [j15]Zhong Yi Wan, Boyko A. Dodov, Christian Lessig, Henk Dijkstra, Themistoklis P. Sapsis:
A data-driven framework for the stochastic reconstruction of small-scale features with application to climate data sets. J. Comput. Phys. 442: 110484 (2021) - [j14]Antoine Blanchard, Themistoklis P. Sapsis:
Output-Weighted Optimal Sampling for Bayesian Experimental Design and Uncertainty Quantification. SIAM/ASA J. Uncertain. Quantification 9(2): 564-592 (2021) - [i13]Yibo Yang, Antoine Blanchard, Themistoklis P. Sapsis, Paris Perdikaris:
Output-Weighted Sampling for Multi-Armed Bandits with Extreme Payoffs. CoRR abs/2102.10085 (2021) - [i12]Alexis-Tzianni Charalampopoulos, Spencer H. Bryngelson, Tim Colonius, Themistoklis P. Sapsis:
Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes and their dynamics. CoRR abs/2110.01374 (2021) - [i11]Samuel H. Rudy, Themistoklis P. Sapsis:
Output-weighted and relative entropy loss functions for deep learning precursors of extreme events. CoRR abs/2112.00825 (2021) - 2020
- [j13]Pantelis-Rafail Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos:
Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics. Neural Networks 126: 191-217 (2020) - [i10]Antoine Blanchard, Themistoklis P. Sapsis:
Bayesian Optimization with Output-Weighted Importance Sampling. CoRR abs/2004.10599 (2020) - [i9]Samuel H. Rudy, Themistoklis P. Sapsis:
Sparse Methods for Automatic Relevance Determination. CoRR abs/2005.08741 (2020) - [i8]Antoine Blanchard, Themistoklis P. Sapsis:
Informative Path Planning for Anomaly Detection in Environment Exploration and Monitoring. CoRR abs/2005.10040 (2020) - [i7]Antoine Blanchard, Themistoklis P. Sapsis:
Output-Weighted Importance Sampling for Bayesian Experimental Design and Uncertainty Quantification. CoRR abs/2006.12394 (2020)
2010 – 2019
- 2019
- [j12]Stephen Guth, Themistoklis P. Sapsis:
Machine Learning Predictors of Extreme Events Occurring in Complex Dynamical Systems. Entropy 21(10): 925 (2019) - [j11]Antoine Blanchard, Themistoklis P. Sapsis:
Analytical Description of Optimally Time-Dependent Modes for Reduced-Order Modeling of Transient Instabilities. SIAM J. Appl. Dyn. Syst. 18(2): 1143-1162 (2019) - [i6]Themistoklis P. Sapsis:
Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples. CoRR abs/1907.07552 (2019) - [i5]Antoine Blanchard, Themistoklis P. Sapsis:
Machine Learning the Tangent Space of Dynamical Instabilities from Data. CoRR abs/1907.10413 (2019) - [i4]Pantelis-Rafail Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos:
Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms. CoRR abs/1910.05266 (2019) - 2018
- [j10]Saviz Mowlavi, Themistoklis P. Sapsis:
Model Order Reduction for Stochastic Dynamical Systems with Continuous Symmetries. SIAM J. Sci. Comput. 40(3) (2018) - [i3]Pantelis-Rafail Vlachas, Wonmin Byeon, Zhong Yi Wan, Themistoklis P. Sapsis, Petros Koumoutsakos:
Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long-Short Term Memory Networks. CoRR abs/1802.07486 (2018) - [i2]Mustafa A. Mohamad, Themistoklis P. Sapsis:
A sequential sampling strategy for extreme event statistics in nonlinear dynamical systems. CoRR abs/1804.07240 (2018) - 2017
- [j9]Mohammad Farazmand, Themistoklis P. Sapsis:
Reduced-order prediction of rogue waves in two-dimensional deep-water waves. J. Comput. Phys. 340: 418-434 (2017) - [j8]Hessam Babaee, Minseok Choi, Themistoklis P. Sapsis, George E. Karniadakis:
A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems. J. Comput. Phys. 344: 303-319 (2017) - [i1]Han Kyul Joo, Mustafa A. Mohamad, Themistoklis P. Sapsis:
Extreme events and their optimal mitigation in nonlinear structural systems excited by stochastic loads: Application to ocean engineering systems. CoRR abs/1706.00676 (2017) - 2016
- [j7]Mustafa A. Mohamad, Will Cousins, Themistoklis P. Sapsis:
A probabilistic decomposition-synthesis method for the quantification of rare events due to internal instabilities. J. Comput. Phys. 322: 288-308 (2016) - 2015
- [j6]Mustafa A. Mohamad, Themistoklis P. Sapsis:
Probabilistic Description of Extreme Events in Intermittently Unstable Dynamical Systems Excited by Correlated Stochastic Processes. SIAM/ASA J. Uncertain. Quantification 3(1): 709-736 (2015) - 2014
- [j5]Minseok Choi, Themistoklis P. Sapsis, George E. Karniadakis:
On the equivalence of dynamically orthogonal and bi-orthogonal methods: Theory and numerical simulations. J. Comput. Phys. 270: 1-20 (2014) - [c2]Will Cousins, Themistoklis P. Sapsis:
Reduced Order Probabilistic Prediction of Rogue Waves in One-Dimensional Envelope Equations. DyDESS 2014: 134-143 - [c1]Mustafa A. Mohamad, Themistoklis P. Sapsis:
Analytical Approximation of the Heavy-Tail Structure for Intermittently Unstable Complex Modes. DyDESS 2014: 144-156 - 2013
- [j4]Mattheus P. Ueckermann, Pierre F. J. Lermusiaux, Themistoklis P. Sapsis:
Numerical schemes for dynamically orthogonal equations of stochastic fluid and ocean flows. J. Comput. Phys. 233: 272-294 (2013) - [j3]Minseok Choi, Themistoklis P. Sapsis, George E. Karniadakis:
A convergence study for SPDEs using combined Polynomial Chaos and Dynamically-Orthogonal schemes. J. Comput. Phys. 245: 281-301 (2013) - [j2]Themistoklis P. Sapsis, Andrew J. Majda:
Blending Modified Gaussian Closure and Non-Gaussian Reduced Subspace Methods for Turbulent Dynamical Systems. J. Nonlinear Sci. 23(6): 1039-1071 (2013) - 2010
- [j1]George Haller, Themistoklis P. Sapsis:
Localized Instability and Attraction along Invariant Manifolds. SIAM J. Appl. Dyn. Syst. 9(2): 611-633 (2010)
Coauthor Index
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