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Yue Yu 0011
Person information
- affiliation: Lehigh University, Department of Department of Mathematics, Bethlehem, PA, USA
- affiliation: Brown University, Division of Applied Mathematics, Providence, RI, USA
Other persons with the same name
- Yue Yu — disambiguation page
- Yue Yu 0001
— National University of Defense Technology, National Laboratory for Parallel and Distributed Processing, China - Yue Yu 0002
— Illinois Institute of Technology, Computer Science Department, Chicago, USA - Yue Yu 0003
— Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, China - Yue Yu 0004
— University of Washington, Department of Aeronautics and Astronautics, Seattle, WA, USA - Yue Yu 0005
— Jilin University, College of Geo-Exploration Science and Technology, Changchun, China (and 1 more) - Yue Yu 0006
— Stanford University, Department of Computer Science, CA, USA - Yue Yu 0007
— Beijing University of Posts and Telecommunications, Beijing, China - Yue Yu 0008
— Tsinghua University, Department of Electronic Engineering, Beijing, China - Yue Yu 0009 — Meta GenAI, Meta Llama Team, USA (and 1 more)
- Yue Yu 0010 — University of California, Irvine (UCI), Department of Computer Science, CA, USA
- Yue Yu 0012
— Mayo Clinic, Department of Quantitative Health Sciences, Rochester, MN, USA (and 1 more) - Yue Yu 0013
— Chengdu University, School of Electronic Information and Electrical Engineering, Sichuan, China (and 1 more)
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2020 – today
- 2025
[j9]Vispi Karkaria
, Doksoo Lee
, Yi-Ping Chen, Yue Yu
, Wei Chen:
An attention-based spatio-temporal neural operator for evolving physics. Mach. Learn. Sci. Technol. 6(2): 45036 (2025)
[j8]Ning Liu
, Siavash Jafarzadeh, Brian Y. Lattimer, Shuna Ni, Jim Lua, Yue Yu
:
Harnessing large language models for data-scarce learning of polymer properties. Nat. Comput. Sci. 5(3): 245-254 (2025)
[i37]Jihong Wang, Xiaochuan Tian, Zhongqiang Zhang, Stewart Silling, Siavash Jafarzadeh, Yue Yu:
Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions. CoRR abs/2505.01060 (2025)
[i36]Ning Liu, Yue Yu:
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery. CoRR abs/2505.23106 (2025)
[i35]Naiyu Yin, Tian Gao, Yue Yu:
Learning Causal Graphs at Scale: A Foundation Model Approach. CoRR abs/2506.18285 (2025)- 2024
[j7]Bian Li, Yue Yu, Xiu Yang
:
The Sparse-Grid-Based Adaptive Spectral Koopman Method. SIAM J. Sci. Comput. 46(5): 2925- (2024)
[c13]Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji:
Effective Causal Discovery under Identifiable Heteroscedastic Noise Model. AAAI 2024: 16486-16494
[c12]Naiyu Yin
, Hanjing Wang
, Yue Yu
, Tian Gao
, Amit Dhurandhar
, Qiang Ji
:
Integrating Markov Blanket Discovery Into Causal Representation Learning for Domain Generalization. ECCV (10) 2024: 271-288
[c11]Ning Liu, Yiming Fan, Xianyi Zeng, Milan Klöwer, Lu Zhang, Yue Yu:
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws. ICML 2024
[c10]Naiyu Yin
, Yue Yu
, Tian Gao
, Qiang Ji:
Efficient Nonlinear DAG Learning Under Projection Framework. ICPR (6) 2024: 445-460
[c9]Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart A. Silling:
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery. NeurIPS 2024
[i34]Siavash Jafarzadeh, Stewart Silling, Ning Liu, Zhongqiang Zhang
, Yue Yu:
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses. CoRR abs/2401.06070 (2024)
[i33]Siavash Jafarzadeh, Stewart Silling, Lu Zhang, Colton J. Ross, Chung-Hao Lee, S. M. Rakibur Rahman, Shuodao Wang, Yue Yu:
Heterogeneous Peridynamic Neural Operators: Discover Biotissue Constitutive Law and Microstructure From Digital Image Correlation Measurements. CoRR abs/2403.18597 (2024)
[i32]Ning Liu, Xuxiao Li, Manoj R. Rajanna, Edward W. Reutzel, Brady Sawyer, Prahalada Rao, Jim Lua, Nam Phan, Yue Yu:
Deep Neural Operator Enabled Digital Twin Modeling for Additive Manufacturing. CoRR abs/2405.09572 (2024)
[i31]Ning Liu, Siavash Jafarzadeh, Brian Y. Lattimer, Shuna Ni, Jim Lua, Yue Yu:
Large language models, physics-based modeling, experimental measurements: the trinity of data-scarce learning of polymer properties. CoRR abs/2407.02770 (2024)
[i30]Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart Silling:
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery. CoRR abs/2408.07307 (2024)
[i29]Ning Liu, Lu Zhang, Tian Gao, Yue Yu:
Disentangled Representation Learning for Parametric Partial Differential Equations. CoRR abs/2410.02136 (2024)
[i28]Yiming Fan, Habib N. Najm, Yue Yu, Stewart Silling, Marta D'Elia:
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators. CoRR abs/2410.20331 (2024)- 2023
[c8]Ning Liu, Yue Yu, Huaiqian You, Neeraj Tatikola:
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation. AISTATS 2023: 6822-6838
[c7]Ning Liu, Siavash Jafarzadeh, Yue Yu:
Domain Agnostic Fourier Neural Operators. NeurIPS 2023
[i27]Huaiqian You, Xiao Xu, Yue Yu, Stewart Silling, Marta D'Elia, John T. Foster:
Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures. CoRR abs/2301.04540 (2023)
[i26]Lu Zhang, Huaiqian You, Tian Gao, Mo Yu, Chung-Hao Lee, Yue Yu:
MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics. CoRR abs/2301.12095 (2023)
[i25]Ning Liu, Siavash Jafarzadeh, Yue Yu:
Domain Agnostic Fourier Neural Operators. CoRR abs/2305.00478 (2023)
[i24]Ning Liu, Yiming Fan, Xianyi Zeng, Milan Klöwer
, Yue Yu:
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws. CoRR abs/2312.11176 (2023)
[i23]Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji:
Causal Discovery under Identifiable Heteroscedastic Noise Model. CoRR abs/2312.12844 (2023)- 2022
[j6]Yiming Fan
, Xiaochuan Tian
, Xiu Yang
, Xingjie Li, Clayton Webster, Yue Yu
:
An asymptotically compatible probabilistic collocation method for randomly heterogeneous nonlocal problems. J. Comput. Phys. 465: 111376 (2022)
[j5]Huaiqian You, Yue Yu
, Marta D'Elia, Tian Gao, Stewart Silling:
Nonlocal kernel network (NKN): A stable and resolution-independent deep neural network. J. Comput. Phys. 469: 111536 (2022)
[c6]Tian Gao, Debarun Bhattacharjya, Elliot Nelson, Miao Liu, Yue Yu:
IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data. ICML 2022: 6988-7001
[i22]Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling:
Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network. CoRR abs/2201.02217 (2022)
[i21]Yiming Fan, Huaiqian You, Xiaochuan Tian, Xiu Yang, Xingjie Li, Naveen Prakash, Yue Yu:
A Meshfree Peridynamic Model for Brittle Fracture in Randomly Heterogeneous Materials. CoRR abs/2202.06578 (2022)
[i20]Minglang Yin, Enrui Zhang, Yue Yu, George Em Karniadakis:
Interfacing Finite Elements with Deep Neural Operators for Fast Multiscale Modeling of Mechanics Problems. CoRR abs/2203.00003 (2022)
[i19]Huaiqian You, Quinn Zhang, Colton J. Ross, Chung-Hao Lee, Yue Yu:
Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling. CoRR abs/2203.08205 (2022)
[i18]Huaiqian You, Quinn Zhang, Colton J. Ross, Chung-Hao Lee, Ming-Chen Hsu, Yue Yu:
A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues from Digital Image Correlation Measurements. CoRR abs/2204.00205 (2022)
[i17]Lu Zhang, Huaiqian You, Yue Yu:
MetaNOR: A Meta-Learnt Nonlocal Operator Regression Approach for Metamaterial Modeling. CoRR abs/2206.02040 (2022)
[i16]Somdatta Goswami, Aniruddha Bora
, Yue Yu, George Em Karniadakis:
Physics-Informed Deep Neural Operator Networks. CoRR abs/2207.05748 (2022)
[i15]Yiming Fan, Marta D'Elia, Yue Yu, Habib N. Najm, Stewart Silling:
Bayesian Nonlocal Operator Regression (BNOR): A Data-Driven Learning Framework of Nonlocal Models with Uncertainty Quantification. CoRR abs/2211.01330 (2022)
[i14]Yiming Fan, Huaiqian You, Yue Yu:
OBMeshfree: An optimization-based meshfree solver for nonlocal diffusion and peridynamics models. CoRR abs/2211.14953 (2022)
[i13]Ning Liu, Yue Yu, Huaiqian You, Neeraj Tatikola:
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation. CoRR abs/2212.14365 (2022)- 2021
[c5]Huaiqian You, Yue Yu, Stewart Silling, Marta D'Elia:
Data-driven Learning of Nonlocal Models: from high-fidelity simulations to constitutive laws. AAAI Spring Symposium: MLPS 2021
[c4]Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji:
DAGs with No Curl: An Efficient DAG Structure Learning Approach. ICML 2021: 12156-12166
[i12]Yue Yu, Huaiqian You, Nathaniel Trask:
An asymptotically compatible treatment of traction loading in linearly elastic peridynamic fracture. CoRR abs/2101.01434 (2021)
[i11]Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji:
DAGs with No Curl: An Efficient DAG Structure Learning Approach. CoRR abs/2106.07197 (2021)
[i10]Yiming Fan, Xiaochuan Tian, Xiu Yang, Xingjie Li, Clayton Webster, Yue Yu:
An asymptotically compatible probabilistic collocation method for randomly heterogeneous nonlocal problems. CoRR abs/2107.01386 (2021)
[i9]Huaiqian You, Yue Yu, Stewart Silling, Marta D'Elia:
A data-driven peridynamic continuum model for upscaling molecular dynamics. CoRR abs/2108.04883 (2021)
[i8]Somdatta Goswami, Minglang Yin, Yue Yu, George E. Karniadakis:
A physics-informed variational DeepONet for predicting the crack path in brittle materials. CoRR abs/2108.06905 (2021)- 2020
[j4]Marta D'Elia, Xiaochuan Tian
, Yue Yu:
A Physically Consistent, Flexible, and Efficient Strategy to Convert Local Boundary Conditions into Nonlocal Volume Constraints. SIAM J. Sci. Comput. 42(4): A1935-A1949 (2020)
[c3]Lu Zhang, Mo Yu, Tian Gao, Yue Yu:
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning. EMNLP (Findings) 2020: 3948-3954
[c2]Dennis Wei, Tian Gao, Yue Yu:
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. NeurIPS 2020
[i7]Huaiqian You, Yue Yu, Nathaniel Trask, Mamikon A. Gulian, Marta D'Elia:
Data-driven learning of robust nonlocal physics from high-fidelity synthetic data. CoRR abs/2005.10076 (2020)
[i6]Lu Zhang, Mo Yu, Tian Gao, Yue Yu:
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning. CoRR abs/2010.01735 (2020)
[i5]Dennis Wei, Tian Gao, Yue Yu:
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. CoRR abs/2010.09133 (2020)
[i4]Huaiqian You, Yue Yu, Stewart Silling, Marta D'Elia:
Data-driven learning of nonlocal models: from high-fidelity simulations to constitutive laws. CoRR abs/2012.04157 (2020)
2010 – 2019
- 2019
[c1]Yue Yu, Jie Chen, Tian Gao, Mo Yu:
DAG-GNN: DAG Structure Learning with Graph Neural Networks. ICML 2019: 7154-7163
[i3]Yue Yu, Jie Chen, Tian Gao, Mo Yu:
DAG-GNN: DAG Structure Learning with Graph Neural Networks. CoRR abs/1904.10098 (2019)
[i2]Huaiqian You, Xin Yang Lu, Nathaniel Trask, Yue Yu:
An Asymptotically Compatible Approach For Neumann-Type Boundary Condition On Nonlocal Problems. CoRR abs/1908.03853 (2019)
[i1]Huaiqian You, Yue Yu, David Kamensky:
An Asymptotically Compatible Formulation for Local-to-Nonlocal Coupling Problems without Overlapping Regions. CoRR abs/1912.06270 (2019)- 2016
[j3]Yue Yu, Paris Perdikaris
, George E. Karniadakis:
Fractional modeling of viscoelasticity in 3D cerebral arteries and aneurysms. J. Comput. Phys. 323: 219-242 (2016)
[j2]Paris Perdikaris
, Joseph A. Insley, Leopold Grinberg, Yue Yu, Michael E. Papka
, George E. Karniadakis:
Visualizing multiphysics, fluid-structure interaction phenomena in intracranial aneurysms. Parallel Comput. 55: 9-16 (2016)- 2013
[j1]Yue Yu, Hyoungsu Baek, George E. Karniadakis:
Generalized fictitious methods for fluid-structure interactions: Analysis and simulations. J. Comput. Phys. 245: 317-346 (2013)
Coauthor Index

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last updated on 2026-01-30 23:22 CET by the dblp team
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