Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
---|---|---|---|
1 |
Material Type: Livro
|
![]() |
Numerical Methods for Ordinary Differential EquationsButcher, J. CNewark: John Wiley & Sons, Incorporated 2016Texto completo disponível |
2 |
Material Type: Artigo
|
![]() |
Solving high-dimensional partial differential equations using deep learningHan, Jiequn ; Jentzen, Arnulf ; E, WeinanProceedings of the National Academy of Sciences - PNAS, 2018-08, Vol.115 (34), p.8505-8510 [Periódico revisado por pares]United States: National Academy of SciencesTexto completo disponível |
3 |
Material Type: Artigo
|
![]() |
DGM: A deep learning algorithm for solving partial differential equationsSirignano, Justin ; Spiliopoulos, KonstantinosJournal of computational physics, 2018-12, Vol.375, p.1339-1364 [Periódico revisado por pares]Cambridge: Elsevier IncTexto completo disponível |
4 |
Material Type: Artigo
|
![]() |
Efficient quantum algorithm for dissipative nonlinear differential equationsLiu, Jin-Peng ; Kolden, Herman Øie ; Krovi, Hari K ; Loureiro, Nuno F ; Trivisa, Konstantina ; Childs, Andrew MProceedings of the National Academy of Sciences - PNAS, 2021-08, Vol.118 (35), p.1 [Periódico revisado por pares]United States: National Academy of SciencesTexto completo disponível |
5 |
Material Type: Livro
|
![]() |
Differential-Algebraic Equations: A Projector Based AnalysisLamour, René ; März, Roswitha ; Tischendorf, CarenBerlin, Heidelberg: Springer-Verlag 2013Texto completo disponível |
6 |
Material Type: Artigo
|
![]() |
Adaptive activation functions accelerate convergence in deep and physics-informed neural networksJagtap, Ameya D. ; Kawaguchi, Kenji ; Karniadakis, George EmJournal of computational physics, 2020-03, Vol.404 (C), p.109136, Article 109136 [Periódico revisado por pares]Cambridge: Elsevier IncTexto completo disponível |
7 |
Material Type: Artigo
|
![]() |
Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential EquationsBeck, Christian ; E, Weinan ; Jentzen, ArnulfJournal of nonlinear science, 2019-08, Vol.29 (4), p.1563-1619 [Periódico revisado por pares]New York: Springer USTexto completo disponível |
8 |
Material Type: Artigo
|
![]() |
Basic Reproduction Ratios for Periodic Abstract Functional Differential Equations (with Application to a Spatial Model for Lyme Disease)Liang, Xing ; Zhang, Lei ; Zhao, Xiao-QiangJournal of dynamics and differential equations, 2019-09, Vol.31 (3), p.1247-1278 [Periódico revisado por pares]New York: Springer USTexto completo disponível |
9 |
Material Type: Artigo
|
![]() |
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equationsRaissi, M. ; Perdikaris, P. ; Karniadakis, G.E.Journal of computational physics, 2019-02, Vol.378, p.686-707 [Periódico revisado por pares]Cambridge: Elsevier IncTexto completo disponível |
10 |
Material Type: Livro
|
![]() |
Functional Analysis, Sobolev Spaces and Partial Differential EquationsBrezis, HaimNew York, NY: Springer Nature 2011Texto completo disponível |