2 citations · 4 across the 6 of their papers we have counts for
6 papers
PDE foundation models are skillful AI weather emulators for the Martian atmosphere
Johannes Schmude, Sujit Roy, Liping Wang +10
We show that AI foundation models that are pretrained on numerical solutions to a diverse corpus of partial differential equations can be adapted and fine-tuned to obtain skillful…
BladeSDF : Unconditional and Conditional Generative Modeling of Representative Blade Geometries Using Signed Distance Functions
Ashish S. Nair, Sandipp Krishnan Ravi, Itzel Salgado +3
Generative AI has emerged as a transformative paradigm in engineering design, enabling automated synthesis and reconstruction of complex 3D geometries while preserving feasibility…
Multi-task Modeling for Engineering Applications with Sparse Data
Yigitcan Comlek, R. Murali Krishnan, Sandipp Krishnan Ravi +7
Modern engineering and scientific workflows often require simultaneous predictions across related tasks and fidelity levels, where high-fidelity data is scarce and expensive, while…
An Uncertainty-aware Deep Learning Framework-based Robust Design Optimization of Metamaterial Units
Zihan Wang, Anindya Bhaduri, Hongyi Xu +1
Mechanical metamaterials represent an innovative class of artificial structures, distinguished by their extraordinary mechanical characteristics, which are beyond the scope of trad…
Heterogenous Multi-Source Data Fusion Through Input Mapping and Latent Variable Gaussian Process
Yigitcan Comlek, Sandipp Krishnan Ravi, Piyush Pandita +3
Artificial intelligence and machine learning frameworks have served as computationally efficient mapping between inputs and outputs for engineering problems. These mappings have en…
Interpretable Multi-Source Data Fusion Through Latent Variable Gaussian Process
Sandipp Krishnan Ravi, Yigitcan Comlek, Arjun Pathak +9
With the advent of artificial intelligence and machine learning, various domains of science and engineering communities have leveraged data-driven surrogates to model complex syste…