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DeepParticle: learning invariant measure by a deep neural network
  minimizing Wasserstein distance on data generated from an interacting
  particle method

DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method

2 November 2021
Zhongjian Wang
Jack Xin
Zhiwen Zhang
ArXivPDFHTML

Papers citing "DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method"

6 / 6 papers shown
Title
Mathematical analysis of singularities in the diffusion model under the
  submanifold assumption
Mathematical analysis of singularities in the diffusion model under the submanifold assumption
Yubin Lu
Zhongjian Wang
G. Bal
DiffM
19
8
0
19 Jan 2023
Accelerating hypersonic reentry simulations using deep learning-based
  hybridization (with guarantees)
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)
Paul Novello
Gaël Poëtte
D. Lugato
S. Peluchon
P. Congedo
AI4CE
6
7
0
27 Sep 2022
A variational neural network approach for glacier modelling with
  nonlinear rheology
A variational neural network approach for glacier modelling with nonlinear rheology
Tiangang Cui
Zhongjian Wang
Zhiwen Zhang
16
4
0
05 Sep 2022
A DeepParticle method for learning and generating aggregation patterns
  in multi-dimensional Keller-Segel chemotaxis systems
A DeepParticle method for learning and generating aggregation patterns in multi-dimensional Keller-Segel chemotaxis systems
Zhongjian Wang
Jack Xin
Zhiwen Zhang
8
5
0
31 Aug 2022
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
203
2,272
0
18 Oct 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and
  Inverse PDE Problems with Noisy Data
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang
Xuhui Meng
George Karniadakis
PINN
170
755
0
13 Mar 2020
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