Nikolaos Evangelou

21 papers Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Enabling probabilistic learning on manifolds through double diffusion maps. J. Comput. Phys. Dimitris G. Giovanis, Nikolaos Evangelou, Ioannis G. Kevrekidis, Roger G. Ghanem
2026	J	`jnl`	Generative learning for slow manifolds and bifurcation diagrams. Comput. Chem. Eng. Ellis R. Crabtree, Dimitris G. Giovanis, Nikolaos Evangelou, Juan M. Bello-Rivas, Ioannis G. Kevrekidis
2025	J	`jnl`	A Mechanistic Analysis of Transformers for Dynamical Systems. CoRR Gregory Duthé, Nikolaos Evangelou, Wei Liu, Ioannis G. Kevrekidis, Eleni N. Chatzi
2025	J	`jnl`	Enabling Probabilistic Learning on Manifolds through Double Diffusion Maps. CoRR Dimitris G. Giovanis, Nikolaos Evangelou, Ioannis G. Kevrekidis, Roger G. Ghanem
2025	J	`jnl`	Generative Learning for Slow Manifolds and Bifurcation Diagrams. CoRR Ellis R. Crabtree, Dimitris G. Giovanis, Nikolaos Evangelou, Juan M. Bello-Rivas, Ioannis G. Kevrekidis
2024	J	`jnl`	Comparing analytic and data-driven approaches to parameter identifiability: A power systems case study. CoRR Nikolaos Evangelou, Alexander M. Stankovic, Ioannis G. Kevrekidis, Mark K. Transtrum
2024	J	`jnl`	From Noise to Signal: Unveiling Treatment Effects from Digital Health Data through Pharmacology-Informed Neural-SDE. CoRR Samira Pakravan, Nikolaos Evangelou, Maxime Usdin, Logan Brooks, James Lu
2024	J	`jnl`	Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era. J. Comput. Phys. Eleni D. Koronaki, Nikolaos Evangelou, Cristina P. Martin-Linares, Edriss S. Titi, Ioannis G. Kevrekidis
2023	J	`jnl`	Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space. J. Comput. Phys. Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis
2023	J	`jnl`	From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics. CoRR Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis, Andreas G. Boudouvis, Ioannis G. Kevrekidis
2023	J	`jnl`	From partial data to out-of-sample parameter and observation estimation with diffusion maps and geometric harmonics. Comput. Chem. Eng. Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis, Andreas G. Boudouvis, Ioannis G. Kevrekidis
2023	J	`jnl`	Machine Learning for the identification of phase-transitions in interacting agent-based systems. CoRR Nikolaos Evangelou, Dimitrios G. Giovanis, George A. Kevrekidis, Grigorios A. Pavliotis, Ioannis G. Kevrekidis
2023	J	`jnl`	Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era. CoRR Eleni D. Koronaki, Nikolaos Evangelou, Cristina P. Martin-Linares, Edriss S. Titi, Ioannis G. Kevrekidis
2023	J	`jnl`	Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points. CoRR Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Cristina P. Martin-Linares, Constantinos I. Siettos, Ioannis G. Kevrekidis
2023	J	`jnl`	Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling. CoRR Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Alexei Makeev, Ioannis G. Kevrekidis
2022	—	`conf`	Bounding Box Based Weakly Supervised Deep Convolutional Neural Network for Medical Image Segmentation Using an Uncertainty Guided and Spatially Constrained Loss. ISBI Golnar K. Mahani, Ruizhe Li, Nikolaos Evangelou, Stamatios Sotiropolous, Paul S. Morgan, Andrew P. French, Xin Chen
2022	J	`jnl`	Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space. CoRR Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis
2022	J	`jnl`	Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles. CoRR Nikolaos Evangelou, Felix Dietrich, Juan M. Bello-Rivas, Alex Yeh, Rachel Stein, Michael A. Bevan, Ioannis G. Kevrekidis
2021	J	`jnl`	Initializing LSTM internal states via manifold learning. CoRR Felix P. Kemeth, Tom Bertalan, Nikolaos Evangelou, Tianqi Cui, Saurabh Malani, Ioannis G. Kevrekidis
2021	J	`jnl`	Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning. CoRR Felix Dietrich, Alexei Makeev, George Kevrekidis, Nikolaos Evangelou, Tom Bertalan, Sebastian Reich, Ioannis G. Kevrekidis
2021	J	`jnl`	On the Parameter Combinations That Matter and on Those That do Not. CoRR Nikolaos Evangelou, Noah J. Wichrowski, George A. Kevrekidis, Felix Dietrich, Mahdi Kooshkbaghi, Sarah McFann, Ioannis G. Kevrekidis