31 citations · 31 across the 2 of their papers we have counts for
5 papers
DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting
Tao Ge, Jaideep Pathak, Akshay Subramaniam +1
Data-driven models, such as FourCastNet (FCN), have shown exemplary performance in high-resolution global weather forecasting. This performance, however, is based on supervision on…
NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework
Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian +7
We present SimNet, an AI-driven multi-physics simulation framework, to accelerate simulations across a wide range of disciplines in science and engineering. Compared to traditional…
ContainerStress: Autonomous Cloud-Node Scoping Framework for Big-Data ML Use Cases
Guang Chao Wang, Kenny Gross, Akshay Subramaniam
Deploying big-data Machine Learning (ML) services in a cloud environment presents a challenge to the cloud vendor with respect to the cloud container configuration sizing for any g…
Turbulence Enrichment using Physics-informed Generative Adversarial Networks
Akshay Subramaniam, Man Long Wong, Raunak D Borker +2
Generative Adversarial Networks (GANs) have been widely used for generating photo-realistic images. A variant of GANs called super-resolution GAN (SRGAN) has already been used succ…
A High-Order Weighted Compact High Resolution Scheme with Boundary Closures for Compressible Turbulent Flows with Shocks
A. Subramaniam, M. L. Wong, S. K. Lele
We present an improved high-order weighted compact high resolution (WCHR) scheme that extends the idea of weighted compact nonlinear schemes (WCNS's) using nonlinear interpolations…