
Improved Memories Learning
We propose Improved Memories Learning (IMeL), a novel algorithm that tur...
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Learning the Effective Dynamics of Complex Multiscale Systems
Simulations of complex multiscale systems are essential for science and ...
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Korali: a HighPerformance Computing Framework for Stochastic Optimization and Bayesian Uncertainty Quantification
We present a modular, opensource, highperformance computing framework ...
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Automating Turbulence Modeling by MultiAgent Reinforcement Learning
The modeling of turbulent flows is critical to scientific and engineerin...
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Mirheo: HighPerformance Mesoscale Simulations for Microfluidics
The transport and manipulation of particles and cells in microfluidic de...
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Optimal sensing for fish school identification
Fish schooling implies an awareness of the swimmers for their companions...
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Forecasting of Spatiotemporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms
How effective are Recurrent Neural Networks (RNNs) in forecasting the sp...
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Machine Learning for Fluid Mechanics
The field of fluid mechanics is rapidly advancing, driven by unprecedent...
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Bending models of lipid bilayer membranes: spontaneous curvature and areadifference elasticity
We preset a computational study of bending models for the curvature elas...
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Remember and Forget for Experience Replay
Experience replay (ER) is crucial for attaining high dataefficiency in ...
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DeepReinforcementLearning for Gliding and Perching Bodies
Controlled gliding is one of the most energetically efficient modes of t...
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Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans and Bayesian Inference
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate su...
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Personalized Radiotherapy Design for Glioblastoma Using Mathematical Models, Multimodal Scans and Bayesian Inference
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate su...
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Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration
Existing radiotherapy (RT) plans for brain tumors derive from population...
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DataDriven Forecasting of HighDimensional Chaotic Systems with LongShort Term Memory Networks
We introduce a datadriven forecasting method for high dimensional, chao...
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Efficient collective swimming by harnessing vortices through deep reinforcement learning
Fish in schooling formations navigate complex flowfields replete with m...
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Fully ContextAware Video Prediction
This paper proposes a new neural network design for unsupervised learnin...
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Bayesian uncertainty quantification for epidemic spread on networks
While there exist a number of mathematical approaches to modeling the sp...
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Optimal fidelity multilevel Monte Carlo for quantification of uncertainty in simulations of cloud cavitation collapse
We quantify uncertainties in the location and magnitude of extreme press...
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Petros Koumoutsakos
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