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ORCIDNikolaos Evangelou
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2020 – today
- 2024
[j3]Eleni D. Koronaki
, Nikolaos Evangelou, Cristina P. Martin-Linares, Edriss S. Titi, Ioannis G. Kevrekidis:
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era. J. Comput. Phys. 506: 112910 (2024)- [i11]Samira Pakravan, Nikolaos Evangelou, Maxime Usdin, Logan Brooks, James Lu:
From Noise to Signal: Unveiling Treatment Effects from Digital Health Data through Pharmacology-Informed Neural-SDE. CoRR abs/2403.03274 (2024) - 2023
- [j2]Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis, Andreas G. Boudouvis, Ioannis G. Kevrekidis:
From partial data to out-of-sample parameter and observation estimation with diffusion maps and geometric harmonics. Comput. Chem. Eng. 178: 108357 (2023) - [j1]Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis:
Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space. J. Comput. Phys. 485: 112072 (2023) - [i10]Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis, Andreas G. Boudouvis, Ioannis G. Kevrekidis:
From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics. CoRR abs/2301.11728 (2023) - [i9]Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Cristina P. Martin-Linares, Constantinos I. Siettos, Ioannis G. Kevrekidis:
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points. CoRR abs/2309.14334 (2023) - [i8]Eleni D. Koronaki, Nikolaos Evangelou, Cristina P. Martin-Linares, Edriss S. Titi, Ioannis G. Kevrekidis:
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era. CoRR abs/2310.15816 (2023) - [i7]Nikolaos Evangelou, Dimitrios G. Giovanis, George A. Kevrekidis, Grigorios A. Pavliotis, Ioannis G. Kevrekidis:
Machine Learning for the identification of phase-transitions in interacting agent-based systems. CoRR abs/2310.19039 (2023) - [i6]Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Alexei Makeev, Ioannis G. Kevrekidis:
Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling. CoRR abs/2311.00797 (2023) - 2022
- [c1]Golnar K. Mahani, Ruizhe Li, Nikolaos Evangelou, Stamatios Sotiropolous, Paul S. Morgan, Andrew P. French, Xin Chen:
Bounding Box Based Weakly Supervised Deep Convolutional Neural Network for Medical Image Segmentation Using an Uncertainty Guided and Spatially Constrained Loss. ISBI 2022: 1-5 - [i5]Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis:
Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space. CoRR abs/2204.12536 (2022) - [i4]Nikolaos Evangelou, Felix Dietrich, Juan M. Bello-Rivas, Alex Yeh, Rachel Stein, Michael A. Bevan, Ioannis G. Kevrekidis:
Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles. CoRR abs/2205.00286 (2022) - 2021
- [i3]Felix P. Kemeth, Tom Bertalan, Nikolaos Evangelou, Tianqi Cui, Saurabh Malani, Ioannis G. Kevrekidis:
Initializing LSTM internal states via manifold learning. CoRR abs/2104.13101 (2021) - [i2]Felix Dietrich, Alexei Makeev, George Kevrekidis, Nikolaos Evangelou, Tom Bertalan, Sebastian Reich, Ioannis G. Kevrekidis:
Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning. CoRR abs/2106.09004 (2021) - [i1]Nikolaos Evangelou, Noah J. Wichrowski, George A. Kevrekidis, Felix Dietrich, Mahdi Kooshkbaghi, Sarah McFann, Ioannis G. Kevrekidis:
On the Parameter Combinations That Matter and on Those That do Not. CoRR abs/2110.06717 (2021)
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