default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLiu Yang 0027
Person information
Other persons with the same name
- Liu Yang — disambiguation page
- Liu Yang 0001 — Yale University, New Haven, CT, USA (and 3 more)
- Liu Yang 0002
![[0000-0001-9915-6432]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-9915-6432")
— Guangzhou University, School of Computer Science and Education Software, China (and 1 more) - Liu Yang 0003 — Chongqing University of Posts and Telecommunications, School of Communication and Information Engineering, China
- Liu Yang 0004 — Army Engineering University of PLA, College of Communication Engineering, Nanjing, China
- Liu Yang 0005 — University of Massachusetts Amherst, College of Information and Computer Sciences, MA, USA
- Liu Yang 0006 — Beijing Jiaotong University, State Key Laboratory of Rail Traffic Control and Safety, China
- Liu Yang 0007 — Beijing Institute of Technology, School of Automation, China
- Liu Yang 0008 — Hong Kong University of Science and Technology, Department of Computer Science and Engineering, Hong Kong
- Liu Yang 0009
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2025
[j10]Liu Yang, Siting Liu, Stanley J. Osher:
Fine-tune language models as multi-modal differential equation solvers. Neural Networks 188: 107455 (2025)- [i15]Elisa Negrini, Yuxuan Liu, Liu Yang, Stanley J. Osher, Hayden Schaeffer:
A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions. CoRR abs/2502.06026 (2025) - 2024
- [j9]Liu Yang, Stanley J. Osher:
PDE generalization of in-context operator networks: A study on 1D scalar nonlinear conservation laws. J. Comput. Phys. 519: 113379 (2024) - [i14]Liu Yang, Stanley J. Osher:
PDE Generalization of In-Context Operator Networks: A Study on 1D Scalar Nonlinear Conservation Laws. CoRR abs/2401.07364 (2024) - [i13]Yadi Cao, Yuxuan Liu, Liu Yang, Rose Yu, Hayden Schaeffer, Stanley J. Osher:
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction. CoRR abs/2411.16063 (2024) - 2023
- [i12]Liu Yang, Siting Liu, Tingwei Meng, Stanley J. Osher:
In-Context Operator Learning for Differential Equation Problems. CoRR abs/2304.07993 (2023) - [i11]Liu Yang, Tingwei Meng, Siting Liu, Stanley J. Osher:
Prompting In-Context Operator Learning with Sensor Data, Equations, and Natural Language. CoRR abs/2308.05061 (2023) - 2022
- [j8]Xuhui Meng, Liu Yang, Zhiping Mao, José del Águila Ferrandis, George Em Karniadakis:
Learning functional priors and posteriors from data and physics. J. Comput. Phys. 457: 111073 (2022) - [j7]Liu Yang, Constantinos Daskalakis, George E. Karniadakis:
Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models. SIAM J. Sci. Comput. 44(1): 80- (2022) - [j6]Liu Yang, George Em Karniadakis:
Potential Flow Generator With L2 Optimal Transport Regularity for Generative Models. IEEE Trans. Neural Networks Learn. Syst. 33(2): 528-538 (2022) - 2021
- [j5]Liu Yang, Xuhui Meng, George Em Karniadakis:
B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data. J. Comput. Phys. 425: 109913 (2021) - [j4]Xiaoli Chen, Liu Yang, Jinqiao Duan, George Em Karniadakis:
Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-Informed Neural Networks. SIAM J. Sci. Comput. 43(3): B811-B830 (2021) - [i10]Liu Yang, Tingwei Meng, George Em Karniadakis:
Measure-conditional Discriminator with Stationary Optimum for GANs and Statistical Distance Surrogates. CoRR abs/2101.06802 (2021) - [i9]Xuhui Meng, Liu Yang, Zhiping Mao, José del Águila Ferrandis, George Em Karniadakis:
Learning Functional Priors and Posteriors from Data and Physics. CoRR abs/2106.05863 (2021) - 2020
- [j3]Liu Yang, Dongkun Zhang, George Em Karniadakis:
Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations. SIAM J. Sci. Comput. 42(1): A292-A317 (2020) - [i8]Dixia Fan, Liu Yang, Michael S. Triantafyllou, George Em Karniadakis:
Reinforcement Learning for Active Flow Control in Experiments. CoRR abs/2003.03419 (2020) - [i7]Liu Yang, Xuhui Meng, George Em Karniadakis:
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data. CoRR abs/2003.06097 (2020) - [i6]Liu Yang, Constantinos Daskalakis, George Em Karniadakis:
Generative Ensemble-Regression: Learning Stochastic Dynamics from Discrete Particle Ensemble Observations. CoRR abs/2008.01915 (2020) - [i5]Xiaoli Chen, Liu Yang, Jinqiao Duan, George Em Karniadakis:
Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-informed Neural Networks. CoRR abs/2008.10653 (2020)
2010 – 2019
- 2019
- [j2]Guofei Pang, Liu Yang, George E. Karniadakis:
Neural-net-induced Gaussian process regression for function approximation and PDE solution. J. Comput. Phys. 384: 270-288 (2019) - [c1]Liu Yang, Prabhat, George E. Karniadakis, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston:
Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs. DLS@SC 2019: 1-11 - [i4]Liu Yang, George E. Karniadakis:
Potential Flow Generator with $L_2$ Optimal Transport Regularity for Generative Models. CoRR abs/1908.11462 (2019) - [i3]Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston, Prabhat, George E. Karniadakis:
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs. CoRR abs/1910.13444 (2019) - 2018
- [j1]Dongkun Zhang, Liu Yang, George E. Karniadakis:
Bi-directional coupling between a PDE-domain and an adjacent Data-domain equipped with multi-fidelity sensors. J. Comput. Phys. 374: 121-134 (2018) - [i2]Guofei Pang, Liu Yang, George E. Karniadakis:
Neural-net-induced Gaussian process regression for function approximation and PDE solution. CoRR abs/1806.11187 (2018) - [i1]Liu Yang, Dongkun Zhang, George E. Karniadakis:
Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations. CoRR abs/1811.02033 (2018)
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 2025-09-23 00:33 CEST 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:
