N. Evangelou

发表

The current state-of-the-art of spinal cord imaging: Methods

Julien Cohen-Adad, Irene Tracey, Massimo Filippi, 2014, NeuroImage.

Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles

Juan M. Bello-Rivas, N. Evangelou, M. A. Bevan, 2022, 2205.00286.

Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space

M. Meilă, I. Kevrekidis, N. Evangelou, 2022, ArXiv.

Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles

Juan M. Bello-Rivas, N. Evangelou, M. A. Bevan, 2022, ArXiv.

On the parameter combinations that matter and on those that do not: data-driven studies of parameter (non)identifiability

Noah J. Wichrowski, I. Kevrekidis, N. Evangelou, 2021, PNAS nexus.

Learning effective stochastic differential equations from microscopic simulations: Linking stochastic numerics to deep learning.

George A. Kevrekidis, I. Kevrekidis, S. Reich, 2021, Chaos.

Comparison of switching to 6-week dosing of natalizumab versus continuing with 4-week dosing in patients with relapsing-remitting multiple sclerosis (NOVA): a randomised, controlled, open-label, phase 3b trial

Jeffrey A. Cohen, Islam M. Zaydan, Gregory F. Wu, 2022, The Lancet Neurology.

From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics

E. D. Koronaki, I. Kevrekidis, N. Evangelou, 2023, Computers & Chemical Engineering.

Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles

Juan M. Bello-Rivas, N. Evangelou, Felix Dietrich, 2022, Molecular Systems Design & Engineering.

Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning pdf

Ioannis G. Kevrekidis, Sebastian Reich, Felix Dietrich, 2021, ArXiv.

Initializing LSTM internal states via manifold learning

Ioannis G. Kevrekidis, Tom Bertalan, Felix P. Kemeth, 2021, Chaos.

The current state-of-the-art of spinal cord imaging: Applications

P. W. Stroman, M. Bacon, J. M. Schwab, 2014, NeuroImage.

Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space

M. Meilă, I. Kevrekidis, N. Evangelou, 2022, J. Comput. Phys..

Efficacy of three neuroprotective drugs in secondary progressive multiple sclerosis (MS-SMART): a phase 2b, multiarm, double-blind, randomised placebo-controlled trial

S. Ourselin, F. Barkhof, D. MacManus, 2020, The Lancet Neurology.

Machine learning-assisted crystal engineering of a zeolite

Noah J. Wichrowski, I. Kevrekidis, N. Evangelou, 2023, Nature communications.

DEMONSTRATING THE PERIVASCULAR DISTRIBUTION OF MS LESIONS IN VIVO WITH 7-TESLA MRI

Jullie W Pan, N. Evangelou, P. Morgan, 2008, Neurology.

Coarse-grained simulations of bidisperse polymer melts

N. Evangelou, D. Theodorou, G. Megariotis, 2021 .

Bounding Box Based Weakly Supervised Deep Convolutional Neural Network for Medical Image Segmentation Using an Uncertainty Guided and Spatially Constrained Loss

Golnar K. Mahani, A. French, P. Morgan, 2022, 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI).

Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points

I. Kevrekidis, N. Evangelou, C. Siettos, 2023, ArXiv.

Machine Learning for the identification of phase-transitions in interacting agent-based systems

George A. Kevrekidis, Dimitrios G. Giovanis, G. Pavliotis, 2023, ArXiv.

Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling

I. Kevrekidis, N. Evangelou, Tianqi Cui, 2023, Chaos.

Task-oriented machine learning surrogates for tipping points of agent-based models

N. Evangelou, Gianluca Fabiani, Cristina P. Martin-Linares, 2024, Nature communications.