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Phase2vec: Dynamical systems embedding with a physics-informed
  convolutional network

Phase2vec: Dynamical systems embedding with a physics-informed convolutional network

7 December 2022
Matthew Ricci
Noa Moriel
Zoe Piran
Mor Nitzan
    AI4CE
ArXivPDFHTML

Papers citing "Phase2vec: Dynamical systems embedding with a physics-informed convolutional network"

3 / 3 papers shown
Title
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for
  Machine Learning and Process-based Hydrology
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
Qingsong Xu
Yilei Shi
Jonathan Bamber
Ye Tuo
Ralf Ludwig
Xiao Xiang Zhu
AI4CE
18
9
0
08 Oct 2023
Controlling nonlinear dynamical systems into arbitrary states using
  machine learning
Controlling nonlinear dynamical systems into arbitrary states using machine learning
Alexander Haluszczynski
Christoph Räth
AI4CE
6
13
0
23 Feb 2021
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
228
31,150
0
16 Jan 2013
1