default search action
Lu Lu 0010
Person information
- affiliation: Brown University, Division of Applied Mathematics, Providence, RI, USA
Other persons with the same name
- Lu Lu — disambiguation page
- Lu Lu 0001
— Chinese Academy of Sciences, Technology and Engineering Center for Space Utilization, Beijing, China (and 2 more)
- Lu Lu 0002
- Lu Lu 0003
- Lu Lu 0004
- Lu Lu 0005
- Lu Lu 0006 — Huazhong University of Science and Technology, Services Computing Technology and System Lab / Big Data Technology and System Lab, China
- Lu Lu 0007
- Lu Lu 0008
- Lu Lu 0009 — LSI Corporation, Milpitas, CA, USA (and 1 more)
- Lu Lu 0011
- Lu Lu 0012
- Lu Lu 0013
- Lu Lu 0014
- Lu Lu 0015
- Lu Lu 0016
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j16]Yuhui Yin, Chenhui Kou, Shengkun Jia
PCDMD: Physics-constrained dynamic mode decomposition for accurate and robust forecasting of dynamical systems with imperfect data and physics. Comput. Phys. Commun. 304: 109303 (2024) - [j15]Zhongyi Jiang
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration. Reliab. Eng. Syst. Saf. 251: 110392 (2024) - [i18]Wensi Wu, Mitchell Daneker, Kevin T. Turner, Matthew A. Jolley, Lu Lu:
Identifying heterogeneous micromechanical properties of biological tissues via physics-informed neural networks. CoRR abs/2402.10741 (2024) - [i17]Anran Jiao, Qile Yan, John Harlim, Lu Lu:
Solving forward and inverse PDE problems on unknown manifolds via physics-informed neural operators. CoRR abs/2407.05477 (2024) - 2023
- [j14]Patricio Clark Di Leoni
Neural operator prediction of linear instability waves in high-speed boundary layers. J. Comput. Phys. 474: 111793 (2023) - [i16]Zhongyi Jiang, Min Zhu, Dongzhuo Li, Qiuzi Li, Yanhua O. Yuan, Lu Lu:
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration. CoRR abs/2303.04778 (2023) - [i15]Benjamin Fan, Edward Qiao, Anran Jiao, Zhouzhou Gu, Wenhao Li, Lu Lu:
Deep Learning for Solving and Estimating Dynamic Macro-Finance Models. CoRR abs/2305.09783 (2023) - 2022
- [j13]Beichuan Deng
Approximation rates of DeepONets for learning operators arising from advection-diffusion equations. Neural Networks 153: 411-426 (2022) - [j12]Pengzhan Jin, Shuai Meng, Lu Lu
MIONet: Learning Multiple-Input Operators via Tensor Product. SIAM J. Sci. Comput. 44(6): 3490- (2022) - [i14]Mitchell Daneker, Zhen Zhang, George Em Karniadakis, Lu Lu:
Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks. CoRR abs/2202.01723 (2022) - [i13]Pengzhan Jin, Shuai Meng, Lu Lu:
MIONet: Learning multiple-input operators via tensor product. CoRR abs/2202.06137 (2022) - [i12]Lu Lu, Raphaël Pestourie, Steven G. Johnson, Giuseppe Romano:
Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transport. CoRR abs/2204.06684 (2022) - [i11]Wensi Wu
Effective Data Sampling Strategies and Boundary Condition Constraints of Physics-Informed Neural Networks for Identifying Material Properties in Solid Mechanics. CoRR abs/2211.15423 (2022) - [i10]Min Zhu, Handi Zhang, Anran Jiao
Reliable extrapolation of deep neural operators informed by physics or sparse observations. CoRR abs/2212.06347 (2022) - 2021
- [j11]Shengze Cai, Zhicheng Wang, Lu Lu
DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks. J. Comput. Phys. 436: 110296 (2021) - [j10]Zhiping Mao, Lu Lu
DeepM&Mnet for hypersonics: Predicting the coupled flow and finite-rate chemistry behind a normal shock using neural-network approximation of operators. J. Comput. Phys. 447: 110698 (2021) - [j9]Lu Lu
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators. Nat. Mach. Intell. 3(3): 218-229 (2021) - [j8]Yixiang Deng
Deep transfer learning and data augmentation improve glucose levels prediction in type 2 diabetes patients. npj Digit. Medicine 4 (2021) - [j7]He Li
How the spleen reshapes and retains young and old red blood cells: A computational investigation. PLoS Comput. Biol. 17(11) (2021) - [j6]Lu Lu
DeepXDE: A Deep Learning Library for Solving Differential Equations. SIAM Rev. 63(1): 208-228 (2021) - [j5]Lu Lu
Physics-Informed Neural Networks with Hard Constraints for Inverse Design. SIAM J. Sci. Comput. 43(6): B1105-B1132 (2021) - [i9]Lu Lu, Raphaël Pestourie, Wenjie Yao, Zhicheng Wang, Francesc Verdugo, Steven G. Johnson:
Physics-informed neural networks with hard constraints for inverse design. CoRR abs/2102.04626 (2021) - [i8]Beichuan Deng, Yeonjong Shin, Lu Lu, Zhongqiang Zhang, George Em Karniadakis:
Convergence rate of DeepONets for learning operators arising from advection-diffusion equations. CoRR abs/2102.10621 (2021) - [i7]Jeremy Yu, Lu Lu, Xuhui Meng, George Em Karniadakis:
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems. CoRR abs/2111.02801 (2021) - 2020
- [j4]Pengzhan Jin, Lu Lu
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness. Neural Networks 130: 85-99 (2020) - [j3]Alireza Yazdani
Systems biology informed deep learning for inferring parameters and hidden dynamics. PLoS Comput. Biol. 16(11) (2020) - [c1]Lu Lu, Xuhui Meng, Zhiping Mao, George Em Karniadakis:
DeepXDE: A Deep Learning Library for Solving Differential Equations. AAAI Spring Symposium: MLPS 2020
2010 – 2019
- 2019
- [j2]Dongkun Zhang, Lu Lu
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems. J. Comput. Phys. 397 (2019) - [j1]Guofei Pang
fPINNs: Fractional Physics-Informed Neural Networks. SIAM J. Sci. Comput. 41(4): A2603-A2626 (2019) - [i6]Lu Lu, Yeonjong Shin, Yanhui Su, George E. Karniadakis:
Dying ReLU and Initialization: Theory and Numerical Examples. CoRR abs/1903.06733 (2019) - [i5]Pengzhan Jin, Lu Lu, Yifa Tang, George E. Karniadakis:
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness. CoRR abs/1905.11427 (2019) - [i4]Lu Lu, Xuhui Meng, Zhiping Mao, George E. Karniadakis:
DeepXDE: A deep learning library for solving differential equations. CoRR abs/1907.04502 (2019) - [i3]Lu Lu, Pengzhan Jin, George Em Karniadakis:
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators. CoRR abs/1910.03193 (2019) - 2018
- [i2]Lu Lu, Yanhui Su, George E. Karniadakis:
Collapse of Deep and Narrow Neural Nets. CoRR abs/1808.04947 (2018) - 2017
- [i1]Yu-Hang Tang, Lu Lu, He Li, Constantinos Evangelinos, Leopold Grinberg, Vipin Sachdeva, George E. Karniadakis:
OpenRBC: A Fast Simulator of Red Blood Cells at Protein Resolution. CoRR abs/1701.02059 (2017)
Coauthor Index
aka: George E. Karniadakis
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-12 20:57 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: