Themistoklis P. Sapsis

50 papers Journal 48Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamics-Informed Deep Learning for Predicting Extreme Events. CoRR Eirini Katsidoniotaki, Themistoklis P. Sapsis
2025	J	`jnl`	Extreme Event Aware (η-) Learning. CoRR Kai Chang, Themistoklis P. Sapsis
2025	J	`jnl`	GEN2: A Generative Prediction-Correction Framework for Long-time Emulations of Spatially-Resolved Climate Extremes. CoRR Mengze Wang, Benedikt Barthel Sorensen, Themistoklis P. Sapsis
2025	J	`jnl`	On Some Tunable Multi-fidelity Bayesian Optimization Frameworks. CoRR Arjun Manoj, Anastasia S. Georgiou, Dimitris G. Giovanis, Themistoklis P. Sapsis, Ioannis G. Kevrekidis
2025	J	`jnl`	Sampling Low-Fidelity Outputs for Estimation of High-Fidelity Density and Its Tails. SIAM/ASA J. Uncertain. Quantification Minji Kim, Kevin O'Connor, Vladas Pipiras, Themistoklis P. Sapsis
2024	J	`jnl`	A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics. CoRR Benedikt Barthel Sorensen, Alexis-Tzianni Charalampopoulos, Shixuan Zhang, Bryce E. Harrop, L. Ruby Leung, Themistoklis P. Sapsis
2024	J	`jnl`	A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data. CoRR Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez, Zhong Yi Wan, Rob Carver, Fei Sha, Themistoklis P. Sapsis
2024	J	`jnl`	Active search for Bifurcations. CoRR Yorgos M. Psarellis, Themistoklis P. Sapsis, Ioannis G. Kevrekidis
2024	J	`jnl`	Information FOMO: The Unhealthy Fear of Missing Out on Information - A Method for Removing Misleading Data for Healthier Models. Entropy Ethan Pickering, Themistoklis P. Sapsis
2024	J	`jnl`	Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages. CoRR Eirini Katsidoniotaki, Biao Su, Eleni Kelasidi, Themistoklis P. Sapsis
2023	J	`jnl`	Active learning for optimal intervention design in causal models. Nat. Mac. Intell. Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler
2023	J	`jnl`	Evaluation of machine learning architectures on the quantification of epistemic and aleatoric uncertainties in complex dynamical systems. CoRR Stephen Guth, Alireza Mojahed, Themistoklis P. Sapsis
2022	J	`jnl`	A Multi-Scale Deep Learning Framework for Projecting Weather Extremes. CoRR Antoine Blanchard, Nishant Parashar, Boyko A. Dodov, Christian Lessig, Themistoklis P. Sapsis
2022	J	`jnl`	Active Learning for Optimal Intervention Design in Causal Models. CoRR Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler
2022	J	`jnl`	Discovering and forecasting extreme events via active learning in neural operators. CoRR Ethan Pickering, George Em Karniadakis, Themistoklis P. Sapsis
2022	J	`jnl`	Discovering and forecasting extreme events via active learning in neural operators. Nat. Comput. Sci. Ethan Pickering, Stephen Guth, George Em Karniadakis, Themistoklis P. Sapsis
2022	J	`jnl`	Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics. SIAM/ASA J. Uncertain. Quantification Hassan Arbabi, Themistoklis P. Sapsis
2022	J	`jnl`	Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models. CoRR Ethan Pickering, Themistoklis P. Sapsis
2022	J	`jnl`	Structure and Distribution Metric for Quantifying the Quality of Uncertainty: Assessing Gaussian Processes, Deep Neural Nets, and Deep Neural Operators for Regression. CoRR Ethan Pickering, Themistoklis P. Sapsis
2021	J	`jnl`	A data-driven framework for the stochastic reconstruction of small-scale features with application to climate data sets. J. Comput. Phys. Zhong Yi Wan, Boyko A. Dodov, Christian Lessig, Henk Dijkstra, Themistoklis P. Sapsis
2021	J	`jnl`	Bayesian optimization with output-weighted optimal sampling. J. Comput. Phys. Antoine Blanchard, Themistoklis P. Sapsis
2021	J	`jnl`	Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes and their dynamics. CoRR Alexis-Tzianni Charalampopoulos, Spencer H. Bryngelson, Tim Colonius, Themistoklis P. Sapsis
2021	J	`jnl`	Output-Weighted Optimal Sampling for Bayesian Experimental Design and Uncertainty Quantification. SIAM/ASA J. Uncertain. Quantification Antoine Blanchard, Themistoklis P. Sapsis
2021	J	`jnl`	Output-Weighted Sampling for Multi-Armed Bandits with Extreme Payoffs. CoRR Yibo Yang, Antoine Blanchard, Themistoklis P. Sapsis, Paris Perdikaris
2021	J	`jnl`	Output-weighted and relative entropy loss functions for deep learning precursors of extreme events. CoRR Samuel H. Rudy, Themistoklis P. Sapsis
2020	J	`jnl`	Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics. Neural Networks Pantelis-Rafail Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos
2020	J	`jnl`	Bayesian Optimization with Output-Weighted Importance Sampling. CoRR Antoine Blanchard, Themistoklis P. Sapsis
2020	J	`jnl`	Informative Path Planning for Anomaly Detection in Environment Exploration and Monitoring. CoRR Antoine Blanchard, Themistoklis P. Sapsis
2020	J	`jnl`	Output-Weighted Importance Sampling for Bayesian Experimental Design and Uncertainty Quantification. CoRR Antoine Blanchard, Themistoklis P. Sapsis
2020	J	`jnl`	Sparse Methods for Automatic Relevance Determination. CoRR Samuel H. Rudy, Themistoklis P. Sapsis
2019	J	`jnl`	Analytical Description of Optimally Time-Dependent Modes for Reduced-Order Modeling of Transient Instabilities. SIAM J. Appl. Dyn. Syst. Antoine Blanchard, Themistoklis P. Sapsis
2019	J	`jnl`	Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms. CoRR Pantelis-Rafail Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos
2019	J	`jnl`	Machine Learning Predictors of Extreme Events Occurring in Complex Dynamical Systems. Entropy Stephen Guth, Themistoklis P. Sapsis
2019	J	`jnl`	Machine Learning the Tangent Space of Dynamical Instabilities from Data. CoRR Antoine Blanchard, Themistoklis P. Sapsis
2019	J	`jnl`	Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples. CoRR Themistoklis P. Sapsis
2018	J	`jnl`	A sequential sampling strategy for extreme event statistics in nonlinear dynamical systems. CoRR Mustafa A. Mohamad, Themistoklis P. Sapsis
2018	J	`jnl`	Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long-Short Term Memory Networks. CoRR Pantelis-Rafail Vlachas, Wonmin Byeon, Zhong Yi Wan, Themistoklis P. Sapsis, Petros Koumoutsakos
2018	J	`jnl`	Model Order Reduction for Stochastic Dynamical Systems with Continuous Symmetries. SIAM J. Sci. Comput. Saviz Mowlavi, Themistoklis P. Sapsis
2017	J	`jnl`	A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems. J. Comput. Phys. Hessam Babaee, Minseok Choi, Themistoklis P. Sapsis, George E. Karniadakis
2017	J	`jnl`	Extreme events and their optimal mitigation in nonlinear structural systems excited by stochastic loads: Application to ocean engineering systems. CoRR Han Kyul Joo, Mustafa A. Mohamad, Themistoklis P. Sapsis
2017	J	`jnl`	Reduced-order prediction of rogue waves in two-dimensional deep-water waves. J. Comput. Phys. Mohammad Farazmand, Themistoklis P. Sapsis
2016	J	`jnl`	A probabilistic decomposition-synthesis method for the quantification of rare events due to internal instabilities. J. Comput. Phys. Mustafa A. Mohamad, Will Cousins, Themistoklis P. Sapsis
2015	J	`jnl`	Probabilistic Description of Extreme Events in Intermittently Unstable Dynamical Systems Excited by Correlated Stochastic Processes. SIAM/ASA J. Uncertain. Quantification Mustafa A. Mohamad, Themistoklis P. Sapsis
2014	—	`conf`	Analytical Approximation of the Heavy-Tail Structure for Intermittently Unstable Complex Modes. DyDESS Mustafa A. Mohamad, Themistoklis P. Sapsis
2014	J	`jnl`	On the equivalence of dynamically orthogonal and bi-orthogonal methods: Theory and numerical simulations. J. Comput. Phys. Minseok Choi, Themistoklis P. Sapsis, George E. Karniadakis
2014	—	`conf`	Reduced Order Probabilistic Prediction of Rogue Waves in One-Dimensional Envelope Equations. DyDESS Will Cousins, Themistoklis P. Sapsis
2013	J	`jnl`	A convergence study for SPDEs using combined Polynomial Chaos and Dynamically-Orthogonal schemes. J. Comput. Phys. Minseok Choi, Themistoklis P. Sapsis, George E. Karniadakis
2013	J	`jnl`	Blending Modified Gaussian Closure and Non-Gaussian Reduced Subspace Methods for Turbulent Dynamical Systems. J. Nonlinear Sci. Themistoklis P. Sapsis, Andrew J. Majda
2013	J	`jnl`	Numerical schemes for dynamically orthogonal equations of stochastic fluid and ocean flows. J. Comput. Phys. Mattheus P. Ueckermann, Pierre F. J. Lermusiaux, Themistoklis P. Sapsis
2010	J	`jnl`	Localized Instability and Attraction along Invariant Manifolds. SIAM J. Appl. Dyn. Syst. George Haller, Themistoklis P. Sapsis