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Fundamental limits to learning closed-form mathematical models from data

Fundamental limits to learning closed-form mathematical models from data

6 April 2022
Oscar Fajardo-Fontiveros
I. Reichardt
Harry R. De Los Ríos
Jordi Duch
M. Sales-Pardo
R. Guimerà
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Papers citing "Fundamental limits to learning closed-form mathematical models from data"

6 / 6 papers shown
Title
A Triumvirate of AI Driven Theoretical Discovery
A Triumvirate of AI Driven Theoretical Discovery
Yang-Hui He
AI4CE
45
4
0
30 May 2024
Generative learning for nonlinear dynamics
Generative learning for nonlinear dynamics
William Gilpin
AI4CE
PINN
60
24
0
07 Nov 2023
Discovering Causal Relations and Equations from Data
Discovering Causal Relations and Equations from Data
Gustau Camps-Valls
Andreas Gerhardus
Urmi Ninad
Gherardo Varando
Georg Martius
E. Balaguer-Ballester
Ricardo Vinuesa
Emiliano Díaz
L. Zanna
Jakob Runge
PINN
AI4Cl
AI4CE
CML
35
72
0
21 May 2023
Active Learning in Symbolic Regression with Physical Constraints
Active Learning in Symbolic Regression with Physical Constraints
Jorge Medina
Andrew D. White
13
3
0
17 May 2023
Is the Machine Smarter than the Theorist: Deriving Formulas for Particle
  Kinematics with Symbolic Regression
Is the Machine Smarter than the Theorist: Deriving Formulas for Particle Kinematics with Symbolic Regression
Zhongtian Dong
K. Kong
Konstantin T. Matchev
Katia Matcheva
46
13
0
15 Nov 2022
Discovering stochastic dynamical equations from biological time series
  data
Discovering stochastic dynamical equations from biological time series data
Arshed Nabeel
Ashwin Karichannavar
Shuaib Palathingal
Jitesh Jhawar
David B. Brückner
M. DannyRaj
Vishwesha Guttal
AI4TS
12
0
0
05 May 2022
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