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

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

26 April 2022
N. Evangelou
Felix Dietrich
E. Chiavazzo
Daniel Lehmberg
M. Meilă
Ioannis G. Kevrekidis
ArXiv (abs)PDFHTML

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

10 / 10 papers shown
Title
Enabling Probabilistic Learning on Manifolds through Double Diffusion Maps
Enabling Probabilistic Learning on Manifolds through Double Diffusion Maps
Dimitris G. Giovanis
N. Evangelou
Ioannis G. Kevrekidis
Roger G. Ghanem
18
0
0
02 Jun 2025
Machine Learning of Slow Collective Variables and Enhanced Sampling via Spatial Techniques
Machine Learning of Slow Collective Variables and Enhanced Sampling via Spatial Techniques
Tuğçe Gökdemir
Jakub Rydzewski
112
2
0
31 Dec 2024
A physics-informed neural network method for the approximation of slow
  invariant manifolds for the general class of stiff systems of ODEs
A physics-informed neural network method for the approximation of slow invariant manifolds for the general class of stiff systems of ODEs
Dimitrios G. Patsatzis
Lucia Russo
Constantinos Siettos
PINN
67
3
0
18 Mar 2024
Tipping Points of Evolving Epidemiological Networks: Machine
  Learning-Assisted, Data-Driven Effective Modeling
Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling
N. Evangelou
Tianqi Cui
J. M. Bello-Rivas
Alexei Makeev
Ioannis G. Kevrekidis
72
1
0
01 Nov 2023
Machine Learning for the identification of phase-transitions in
  interacting agent-based systems: a Desai-Zwanzig example
Machine Learning for the identification of phase-transitions in interacting agent-based systems: a Desai-Zwanzig example
N. Evangelou
Dimitrios G. Giovanis
George A. Kevrekidis
G. Pavliotis
Ioannis G. Kevrekidis
72
0
0
29 Oct 2023
Nonlinear dimensionality reduction then and now: AIMs for dissipative
  PDEs in the ML era
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era
E. D. Koronaki
N. Evangelou
Cristina P. Martin-Linares
E. Titi
Ioannis G. Kevrekidis
50
6
0
24 Oct 2023
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping
  Points
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points
Gianluca Fabiani
N. Evangelou
Tianqi Cui
J. M. Bello-Rivas
Cristina P. Martin-Linares
Constantinos Siettos
Ioannis G. Kevrekidis
64
2
0
25 Sep 2023
Early warning indicators via latent stochastic dynamical systems
Early warning indicators via latent stochastic dynamical systems
Lingyu Feng
Ting Gao
Wang Xiao
Jinqiao Duan
61
3
0
07 Sep 2023
Data-driven modelling of brain activity using neural networks, Diffusion
  Maps, and the Koopman operator
Data-driven modelling of brain activity using neural networks, Diffusion Maps, and the Koopman operator
I. Gallos
Daniel Lehmberg
Felix Dietrich
Constantinos Siettos
61
8
0
24 Apr 2023
Data-driven Control of Agent-based Models: an Equation/Variable-free
  Machine Learning Approach
Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach
Dimitrios G. Patsatzis
Lucia Russo
Ioannis G. Kevrekidis
Constantinos Siettos
59
15
0
12 Jul 2022
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