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Data-driven Control of Agent-based Models: an Equation/Variable-free
  Machine Learning Approach
v1v2 (latest)

Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach

12 July 2022
Dimitrios G. Patsatzis
Lucia Russo
Ioannis G. Kevrekidis
Constantinos Siettos
ArXiv (abs)PDFHTML

Papers citing "Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach"

13 / 13 papers shown
Title
Data-driven control of spatiotemporal chaos with reduced-order neural
  ODE-based models and reinforcement learning
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning
Kevin Zeng
Alec J. Linot
M. Graham
AI4CE
66
29
0
01 May 2022
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
N. Evangelou
Felix Dietrich
E. Chiavazzo
Daniel Lehmberg
M. Meilă
Ioannis G. Kevrekidis
51
23
0
26 Apr 2022
Solving and Learning Nonlinear PDEs with Gaussian Processes
Solving and Learning Nonlinear PDEs with Gaussian Processes
Yifan Chen
Bamdad Hosseini
H. Owhadi
Andrew M. Stuart
79
157
0
24 Mar 2021
Learning the solution operator of parametric partial differential
  equations with physics-informed DeepOnets
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Sizhuang He
Hanwen Wang
P. Perdikaris
AI4CE
102
710
0
19 Mar 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
516
2,456
0
18 Oct 2020
Multiscale Simulations of Complex Systems by Learning their Effective
  Dynamics
Multiscale Simulations of Complex Systems by Learning their Effective Dynamics
Pantelis R. Vlachas
G. Arampatzis
Caroline Uhler
Petros Koumoutsakos
AI4CE
91
150
0
24 Jun 2020
DPM: A deep learning PDE augmentation method (with application to
  large-eddy simulation)
DPM: A deep learning PDE augmentation method (with application to large-eddy simulation)
Jonathan B Freund
J. MacArt
Justin A. Sirignano
AI4CE
165
136
0
20 Nov 2019
Deep least-squares methods: an unsupervised learning-based numerical
  method for solving elliptic PDEs
Deep least-squares methods: an unsupervised learning-based numerical method for solving elliptic PDEs
Z. Cai
Jingshuang Chen
Min Liu
Xinyu Liu
64
90
0
05 Nov 2019
DeepONet: Learning nonlinear operators for identifying differential
  equations based on the universal approximation theorem of operators
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Lu Lu
Pengzhan Jin
George Karniadakis
248
2,162
0
08 Oct 2019
DeepXDE: A deep learning library for solving differential equations
DeepXDE: A deep learning library for solving differential equations
Lu Lu
Xuhui Meng
Zhiping Mao
George Karniadakis
PINNAI4CE
101
1,549
0
10 Jul 2019
Molecular enhanced sampling with autoencoders: On-the-fly collective
  variable discovery and accelerated free energy landscape exploration
Molecular enhanced sampling with autoencoders: On-the-fly collective variable discovery and accelerated free energy landscape exploration
Wei Chen
Andrew L. Ferguson
66
200
0
30 Dec 2017
Hidden Physics Models: Machine Learning of Nonlinear Partial
  Differential Equations
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations
M. Raissi
George Karniadakis
AI4CEPINN
84
1,143
0
02 Aug 2017
A Nonlinear Dimensionality Reduction Framework Using Smooth Geodesics
A Nonlinear Dimensionality Reduction Framework Using Smooth Geodesics
Kelum Gajamannage
Randy Paffenroth
Erik Bollt
50
28
0
21 Jul 2017
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