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ORCIDYue 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
![[0000-0002-9865-2212]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-9865-2212")
— 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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