Nikolaos Evangelou

According to our database, Nikolaos Evangelou authored at least 13 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era.

Eleni D. Koronaki, Nikolaos Evangelou, Cristina P. Martin-Linares, Edriss S. Titi, Ioannis G. Kevrekidis

J. Comput. Phys., 2024

Comparing analytic and data-driven approaches to parameter identifiability: A power systems case study.

Nikolaos Evangelou, Alexander M. Stankovic, Ioannis G. Kevrekidis, Mark K. Transtrum

CoRR, 2024

From Noise to Signal: Unveiling Treatment Effects from Digital Health Data through Pharmacology-Informed Neural-SDE.

Samira Pakravan, Nikolaos Evangelou, Maxime Usdin, Logan Brooks, James Lu

CoRR, 2024

2023

From partial data to out-of-sample parameter and observation estimation with diffusion maps and geometric harmonics.

Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis, Andreas G. Boudouvis, Ioannis G. Kevrekidis

Comput. Chem. Eng., October, 2023

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space.

Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis

J. Comput. Phys., 2023

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

Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Alexei Makeev, Ioannis G. Kevrekidis

CoRR, 2023

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

Nikolaos Evangelou, Dimitrios G. Giovanis, George A. Kevrekidis, Grigorios A. Pavliotis, Ioannis G. Kevrekidis

CoRR, 2023

Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points.

Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Cristina P. Martin-Linares, Constantinos I. Siettos, Ioannis G. Kevrekidis

CoRR, 2023

2022

Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles.

Nikolaos Evangelou, Felix Dietrich, Juan M. Bello-Rivas, Alex Yeh, Rachel Stein, Michael A. Bevan, Ioannis G. Kevrekidis

CoRR, 2022

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

Golnar K. Mahani, Ruizhe Li, Nikolaos Evangelou, Stamatios Sotiropolous, Paul S. Morgan, Andrew P. French, Xin Chen

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021

On the Parameter Combinations That Matter and on Those That do Not.

Nikolaos Evangelou, Noah J. Wichrowski, George A. Kevrekidis, Felix Dietrich, Mahdi Kooshkbaghi, Sarah McFann, Ioannis G. Kevrekidis

CoRR, 2021

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

Felix Dietrich, Alexei Makeev, George Kevrekidis, Nikolaos Evangelou, Tom Bertalan, Sebastian Reich, Ioannis G. Kevrekidis

CoRR, 2021

Initializing LSTM internal states via manifold learning.

Felix P. Kemeth, Tom Bertalan, Nikolaos Evangelou, Tianqi Cui, Saurabh Malani, Ioannis G. Kevrekidis

CoRR, 2021