ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2504.07085
  4. Cited By
Identifying Unknown Stochastic Dynamics via Finite expression methods
v1v2v3 (latest)

Identifying Unknown Stochastic Dynamics via Finite expression methods

9 April 2025
Senwei Liang
Chunmei Wang
Xingjian Xu
ArXiv (abs)PDFHTML

Papers citing "Identifying Unknown Stochastic Dynamics via Finite expression methods"

16 / 16 papers shown
Title
Learning Epidemiological Dynamics via the Finite Expression Method
Learning Epidemiological Dynamics via the Finite Expression MethodJournal of Machine Learning for Modeling and Computing (JMLMC), 2024
Jianda Du
Senwei Liang
Chunmei Wang
160
1
0
31 Dec 2024
A Training-Free Conditional Diffusion Model for Learning Stochastic
  Dynamical Systems
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical SystemsSIAM Journal on Scientific Computing (SISC), 2024
Yanfang Liu
Yuán Chen
Dongbin Xiu
Guannan Zhang
DiffM
254
9
0
04 Oct 2024
KAN: Kolmogorov-Arnold Networks
KAN: Kolmogorov-Arnold Networks
Ziming Liu
Yixuan Wang
Sachin Vaidya
Fabian Ruehle
James Halverson
Marin Soljacic
Thomas Y. Hou
Max Tegmark
900
1,162
0
30 Apr 2024
Symbolic Regression via Control Variable Genetic Programming
Symbolic Regression via Control Variable Genetic Programming
Nan Jiang
Yexiang Xue
108
13
0
25 May 2023
Finite Expression Methods for Discovering Physical Laws from Data
Finite Expression Methods for Discovering Physical Laws from Data
Zhongyi Jiang
Chunmei Wang
Haizhao Yang
162
8
0
15 May 2023
Learning Stochastic Dynamical System via Flow Map Operator
Learning Stochastic Dynamical System via Flow Map OperatorJournal of Computational Physics (JCP), 2023
Yuán Chen
D. Xiu
AI4CE
186
26
0
05 May 2023
Genetic Programming Based Symbolic Regression for Analytical Solutions
  to Differential Equations
Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations
Hongsup Oh
R. Amici
Geoffrey F. Bomarito
Shandian Zhe
Robert M. Kirby
Jacob Hochhalter
137
7
0
07 Feb 2023
Finite Expression Method for Solving High-Dimensional Partial Differential Equations
Finite Expression Method for Solving High-Dimensional Partial Differential Equations
Senwei Liang
Haizhao Yang
298
21
0
21 Jun 2022
End-to-end symbolic regression with transformers
End-to-end symbolic regression with transformersNeural Information Processing Systems (NeurIPS), 2022
Pierre-Alexandre Kamienny
Stéphane dÁscoli
Guillaume Lample
Franccois Charton
221
226
0
22 Apr 2022
Stationary Density Estimation of Itô Diffusions Using Deep Learning
Stationary Density Estimation of Itô Diffusions Using Deep Learning
Yiqi Gu
J. Harlim
Senwei Liang
Haizhao Yang
158
15
0
09 Sep 2021
Discovering Symbolic Models from Deep Learning with Inductive Biases
Discovering Symbolic Models from Deep Learning with Inductive Biases
M. Cranmer
Alvaro Sanchez-Gonzalez
Peter W. Battaglia
Rui Xu
Kyle Cranmer
D. Spergel
S. Ho
AI4CE
301
566
0
19 Jun 2020
Deep symbolic regression: Recovering mathematical expressions from data
  via risk-seeking policy gradients
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradientsInternational Conference on Learning Representations (ICLR), 2019
Brenden K. Petersen
Mikel Landajuela
T. Nathan Mundhenk
Claudio Santiago
Soo K. Kim
Joanne T. Kim
426
393
0
10 Dec 2019
AI Feynman: a Physics-Inspired Method for Symbolic Regression
AI Feynman: a Physics-Inspired Method for Symbolic RegressionScience Advances (Sci Adv), 2019
S. Udrescu
Max Tegmark
423
1,051
0
27 May 2019
Bag of Tricks for Image Classification with Convolutional Neural
  Networks
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He
Zhi-Li Zhang
Hang Zhang
Zhongyue Zhang
Junyuan Xie
Mu Li
618
1,523
0
04 Dec 2018
Data Driven Governing Equations Approximation Using Deep Neural Networks
Data Driven Governing Equations Approximation Using Deep Neural Networks
Tong Qin
Kailiang Wu
D. Xiu
PINN
183
289
0
13 Nov 2018
Improved Techniques for Training GANs
Improved Techniques for Training GANs
Tim Salimans
Ian Goodfellow
Wojciech Zaremba
Vicki Cheung
Alec Radford
Xi Chen
GAN
1.3K
9,784
0
10 Jun 2016
1