Zobrazeno 1 - 10
of 11 848
pro vyhledávání: '"Barati, A."'
Recent advances in deep learning have inspired numerous works on data-driven solutions to partial differential equation (PDE) problems. These neural PDE solvers can often be much faster than their numerical counterparts; however, each presents its un
Externí odkaz:
http://arxiv.org/abs/2410.01153
Autor:
Lorsung, Cooper, Farimani, Amir Barati
Solving Partial Differential Equations (PDEs) is ubiquitous in science and engineering. Computational complexity and difficulty in writing numerical solvers has motivated the development of machine learning techniques to generate solutions quickly. M
Externí odkaz:
http://arxiv.org/abs/2410.01137
Autor:
Ogoke, Francis, Suresh, Sumesh Kalambettu, Adamczyk, Jesse, Bolintineanu, Dan, Garland, Anthony, Heiden, Michael, Farimani, Amir Barati
The stochastic formation of defects during Laser Powder Bed Fusion (L-PBF) negatively impacts its adoption for high-precision use cases. Optical monitoring techniques can be used to identify defects based on layer-wise imaging, but these methods are
Externí odkaz:
http://arxiv.org/abs/2409.13171
As robotic systems become increasingly integrated into complex real-world environments, there is a growing need for approaches that enable robots to understand and act upon natural language instructions without relying on extensive pre-programmed kno
Externí odkaz:
http://arxiv.org/abs/2409.11580
Autor:
Kuan, Desmond, Farimani, Amir Barati
The adaptive immune response, largely mediated by B-cell receptors (BCRs), plays a crucial role for effective pathogen neutralization due to its diversity and antigen specificity. Designing BCRs de novo, or from scratch, has been challenging because
Externí odkaz:
http://arxiv.org/abs/2409.06090
Autor:
Graves, Reid, Farimani, Amir Barati
The design of aerodynamic shapes, such as airfoils, has traditionally required significant computational resources and relied on predefined design parameters, which limit the potential for novel shape synthesis. In this work, we introduce a data-driv
Externí odkaz:
http://arxiv.org/abs/2408.15898
Industry 4.0 has revolutionized manufacturing by driving digitalization and shifting the paradigm toward additive manufacturing (AM). Fused Deposition Modeling (FDM), a key AM technology, enables the creation of highly customized, cost-effective prod
Externí odkaz:
http://arxiv.org/abs/2408.14307
Autor:
Shu, Dule, Farimani, Amir Barati
The success of diffusion probabilistic models in generative tasks, such as text-to-image generation, has motivated the exploration of their application to regression problems commonly encountered in scientific computing and various other domains. In
Externí odkaz:
http://arxiv.org/abs/2408.04718
L2AI: lightweight three-factor authentication and authorization in IOMT blockchain-based environment
Medical Internet of Things (IoMT) is the next frontier in the digital revolution and is utilized in healthcare. In this context, IoT enables individuals to remotely manage their essential activities with minimal interaction. However, the limitations
Externí odkaz:
http://arxiv.org/abs/2407.12187
There has recently been increasing attention towards developing foundational neural Partial Differential Equation (PDE) solvers and neural operators through large-scale pretraining. However, unlike vision and language models that make use of abundant
Externí odkaz:
http://arxiv.org/abs/2407.17616