INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation. - Ning Liu 019; Yue Yu 011; Huaiqian You; Neeraj Tatikola (AISTATS, 2023)

Domain Agnostic Fourier Neural Operators. - Ning Liu 019; Siavash Jafarzadeh; Yue Yu 011 (NeurIPS, 2023)

Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws. - Ning Liu 019; Yiming Fan 001; Xianyi Zeng; Milan Klöwer; Yue Yu 011 (CoRR, 2023)

Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws. - Ning Liu 019; Yiming Fan 001; Xianyi Zeng; Milan Klöwer; Lu Zhang; Yue Yu 011 (ICML, 2024)

Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery. - Yue Yu 011; Ning Liu 019; Fei Lu; Tian Gao 007; Siavash Jafarzadeh; Stewart A. Silling (NeurIPS, 2024)

Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses. - Siavash Jafarzadeh; Stewart Silling; Ning Liu 019; Zhongqiang Zhang 003; Yue Yu 011 (CoRR, 2024)

Deep Neural Operator Enabled Digital Twin Modeling for Additive Manufacturing. - Ning Liu 019; Xuxiao Li; Manoj R. Rajanna; Edward W. Reutzel; Brady Sawyer; Prahalada Rao; Jim Lua; Nam Phan; Yue Yu 011 (CoRR, 2024)

Large language models, physics-based modeling, experimental measurements: the trinity of data-scarce learning of polymer properties. - Ning Liu 019; Siavash Jafarzadeh; Brian Y. Lattimer; Shuna Ni; Jim Lua; Yue Yu 011 (CoRR, 2024)

Disentangled Representation Learning for Parametric Partial Differential Equations. - Ning Liu 019; Lu Zhang; Tian Gao 007; Yue Yu 011 (CoRR, 2024)

Harnessing large language models for data-scarce learning of polymer properties. - Ning Liu 019; Siavash Jafarzadeh; Brian Y. Lattimer; Shuna Ni; Jim Lua; Yue Yu 011 (Nat. Comput. Sci., 2025)

Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery. - Ning Liu 019; Yue Yu 011 (CoRR, 2025)