Themistoklis P. Sapsis

Orcid: 0000-0003-0302-0691

According to our database1, Themistoklis P. Sapsis authored at least 43 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data.
CoRR, 2024

Active search for Bifurcations.
CoRR, 2024

Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages.
CoRR, 2024

A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics.
CoRR, 2024

2023
Active learning for optimal intervention design in causal models.
Nat. Mac. Intell., October, 2023

Evaluation of machine learning architectures on the quantification of epistemic and aleatoric uncertainties in complex dynamical systems.
CoRR, 2023

2022
Discovering and forecasting extreme events via active learning in neural operators.
Nat. Comput. Sci., 2022

Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics.
SIAM/ASA J. Uncertain. Quantification, 2022

A Multi-Scale Deep Learning Framework for Projecting Weather Extremes.
CoRR, 2022

Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models.
CoRR, 2022

Discovering and forecasting extreme events via active learning in neural operators.
CoRR, 2022

Structure and Distribution Metric for Quantifying the Quality of Uncertainty: Assessing Gaussian Processes, Deep Neural Nets, and Deep Neural Operators for Regression.
CoRR, 2022

2021
Output-Weighted Optimal Sampling for Bayesian Experimental Design and Uncertainty Quantification.
SIAM/ASA J. Uncertain. Quantification, 2021

A data-driven framework for the stochastic reconstruction of small-scale features with application to climate data sets.
J. Comput. Phys., 2021

Bayesian optimization with output-weighted optimal sampling.
J. Comput. Phys., 2021

Output-weighted and relative entropy loss functions for deep learning precursors of extreme events.
CoRR, 2021

Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes and their dynamics.
CoRR, 2021

Output-Weighted Sampling for Multi-Armed Bandits with Extreme Payoffs.
CoRR, 2021

2020
Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics.
Neural Networks, 2020

Output-Weighted Importance Sampling for Bayesian Experimental Design and Uncertainty Quantification.
CoRR, 2020

Informative Path Planning for Anomaly Detection in Environment Exploration and Monitoring.
CoRR, 2020

Sparse Methods for Automatic Relevance Determination.
CoRR, 2020

Bayesian Optimization with Output-Weighted Importance Sampling.
CoRR, 2020

2019
Analytical Description of Optimally Time-Dependent Modes for Reduced-Order Modeling of Transient Instabilities.
SIAM J. Appl. Dyn. Syst., 2019

Machine Learning Predictors of Extreme Events Occurring in Complex Dynamical Systems.
Entropy, 2019

Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms.
CoRR, 2019

Machine Learning the Tangent Space of Dynamical Instabilities from Data.
CoRR, 2019

Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples.
CoRR, 2019

2018
Model Order Reduction for Stochastic Dynamical Systems with Continuous Symmetries.
SIAM J. Sci. Comput., 2018

A sequential sampling strategy for extreme event statistics in nonlinear dynamical systems.
CoRR, 2018

Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long-Short Term Memory Networks.
CoRR, 2018

2017
Reduced-order prediction of rogue waves in two-dimensional deep-water waves.
J. Comput. Phys., 2017

A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems.
J. Comput. Phys., 2017

Extreme events and their optimal mitigation in nonlinear structural systems excited by stochastic loads: Application to ocean engineering systems.
CoRR, 2017

2016
A probabilistic decomposition-synthesis method for the quantification of rare events due to internal instabilities.
J. Comput. Phys., 2016

2015
Probabilistic Description of Extreme Events in Intermittently Unstable Dynamical Systems Excited by Correlated Stochastic Processes.
SIAM/ASA J. Uncertain. Quantification, 2015

2014
On the equivalence of dynamically orthogonal and bi-orthogonal methods: Theory and numerical simulations.
J. Comput. Phys., 2014

Analytical Approximation of the Heavy-Tail Structure for Intermittently Unstable Complex Modes.
Proceedings of the Dynamic Data-Driven Environmental Systems Science, 2014

Reduced Order Probabilistic Prediction of Rogue Waves in One-Dimensional Envelope Equations.
Proceedings of the Dynamic Data-Driven Environmental Systems Science, 2014

2013
Blending Modified Gaussian Closure and Non-Gaussian Reduced Subspace Methods for Turbulent Dynamical Systems.
J. Nonlinear Sci., 2013

Numerical schemes for dynamically orthogonal equations of stochastic fluid and ocean flows.
J. Comput. Phys., 2013

A convergence study for SPDEs using combined Polynomial Chaos and Dynamically-Orthogonal schemes.
J. Comput. Phys., 2013

2010
Localized Instability and Attraction along Invariant Manifolds.
SIAM J. Appl. Dyn. Syst., 2010


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