32 citations · 54 across the 11 of their papers we have counts for
5 papers · 1 filter
Group Downsampling with Equivariant Anti-aliasing
Md Ashiqur Rahman, Raymond A. Yeh
Downsampling layers are crucial building blocks in CNN architectures, which help to increase the receptive field for learning high-level features and reduce the amount of memory/co…
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy +9
Existing neural operator architectures face challenges when solving multiphysics problems with coupled partial differential equations (PDEs) due to complex geometries, interactions…
Truly Scale-Equivariant Deep Nets with Fourier Layers
Md Ashiqur Rahman, Raymond A. Yeh
In computer vision, models must be able to adapt to changes in image resolution to effectively carry out tasks such as image segmentation; This is known as scale-equivariance. Rece…
Generative Adversarial Neural Operators
Md Ashiqur Rahman, Manuel A. Florez, Anima Anandkumar +2
We propose the generative adversarial neural operator (GANO), a generative model paradigm for learning probabilities on infinite-dimensional function spaces. The natural sciences a…
U-NO: U-shaped Neural Operators
Md Ashiqur Rahman, Zachary E. Ross, Kamyar Azizzadenesheli
Neural operators generalize classical neural networks to maps between infinite-dimensional spaces, e.g., function spaces. Prior works on neural operators proposed a series of novel…