Deep Learning Beyond CS

简介

关注

DL+Numerical PDE

Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, Ken PerlinACCELERATING EULERIAN FLUID SIMULATION WITH CONVOLUTIONAL NETWORKS
ICLR2017 workshop version:link
Jiequn Han, Weinan E.Deep Learning Approximation for Stochastic Control Problems arxiv
Hoping approximation by neural network can overcome the curse of dimensionality to solve PDE in high dimensional space.
Jiequn Han, Arnulf Jentzen, Weinan E.Overcoming the curse of dimensionality: Solving high-dimensional partial differential equations using deep learning arxiv
longer version.
J.Nagoor Kani, Ahmed H. Elsheikh.DR-RNN: A deep residual recurrent neural network for model reduction arXiv
Designed a physic based RNN with residual connection to do model reduction.(Reduce the dimension for a dynamic.)
Weinan E, Bing YuThe Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems. arXiv:1710.00211
Christian Beck, Weinan E, Arnulf Jentzen Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations.
Masaaki Fujii, Akihiko Takahashi, Masayuki Takahashi.Asymptotic Expansion as Prior Knowledge in Deep Learning Method for high dimensional BSDEs
Zichao long, Yiping Lu, Xianzhong Ma, Bin Dong. PDE-Net:Learning PDEs From Data
Jens Berg, Kaj NyströmA unified deep artificial neural network approach to partial differential equations in complex geometries
arXiv
Emmanuel de Bezenac, Arthur Pajot, Patrick Gallinari Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge
arXiv
Ronan Fablet, Said Ouala, Cedric Herzet Bilinear residual Neural Network for the identification and forecasting of dynamical systems arXiv
Y. Khoo, J. Lu, and L. Ying. Solving parametric PDE problems with artificial neural networks. pdf
Linfeng Zhang, Han Wang, Weinan E Reinforced dynamics for enhanced sampling in large atomic and molecular systems. I. Basic MethodologyarXiv
Maziar Raissi, Paris Perdikaris, George Em Karniadakis Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations arXiv2 arXiv(part2)

Ref: http://about.2prime.cn/pde.html (@陆一平-北京大学-数学 )

创建: Apr 27, 2018 | 13:45

Deep Learning Beyond CS

目录

DL+Numerical PDE

DL+Physics

Dynamic Perspective Of DL

DL+Astronomy