70 citations · 137 across the 10 of their papers we have counts for
5 papers · 1 filter
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery
Yue Yu, Ning Liu, Fei Lu +3
Despite the recent popularity of attention-based neural architectures in core AI fields like natural language processing (NLP) and computer vision (CV), their potential in modeling…
Large language models, physics-based modeling, experimental measurements: the trinity of data-scarce learning of polymer properties
Ning Liu, Siavash Jafarzadeh, Brian Y. Lattimer +3
Large language models (LLMs) bear promise as a fast and accurate material modeling paradigm for evaluation, analysis, and design. Their vast number of trainable parameters necessit…
An Ultra-high-speed Reproducing Kernel Particle Method
Siavash Jafarzadeh, Michael Hillman
In this work, the fast-convolving reproducing kernel particle method (FC-RKPM) is introduced. This method is hundreds to millions of times faster than the traditional RKPM for 3D m…
Heterogeneous Peridynamic Neural Operators: Discover Biotissue Constitutive Law and Microstructure From Digital Image Correlation Measurements
Siavash Jafarzadeh, Stewart Silling, Lu Zhang +5
Human tissues are highly organized structures with collagen fiber arrangements varying from point to point. Anisotropy of the tissue arises from the natural orientation of the fibe…
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses
Siavash Jafarzadeh, Stewart Silling, Ning Liu +2
Neural operators, which can act as implicit solution operators of hidden governing equations, have recently become popular tools for learning the responses of complex real-world ph…