activity
20232026
most citedPretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs

4 citations · 5 across the 5 of their papers we have counts for

collaborators

8 papers

cs.RO2026

SkipVLA: Skipping VLA Steps with Classical Planning for Fast Robot Manipulation

Kaivalya Agrawal, Md Ashiqur Rahman, Raymond A. Yeh +1

Vision-Language-Action (VLA) models are a class of generalist robot policies that map camera images and language instructions directly to robot actions. While promising, these mode…

cs.CV2026

Helix4D: Complex 4D Mesh Generation

Jiraphon Yenphraphai, Jianqi Chen, Jian Wang +6

Current video-to-4D methods struggle with complex topology changes, transparent materials, thin structures, and inner surfaces. We present Helix4D, a dynamic mesh generation framew…

cs.CV2026

Tunable Soft Equivariance with Guarantees

Md Ashiqur Rahman, Lim Jun Hao, Jeremiah Jiang +2

Equivariance is a fundamental property in computer vision models, yet strict equivariance is rarely satisfied in real-world data, which can limit a model's performance. Controlling…

cs.CV2025

CLIPSym: Delving into Symmetry Detection with CLIP

Tinghan Yang, Md Ashiqur Rahman, Raymond A. Yeh

Symmetry is one of the most fundamental geometric cues in computer vision, and detecting it has been an ongoing challenge. With the recent advances in vision-language models,~i.e.,…

cs.CV2025

Local Scale Equivariance with Latent Deep Equilibrium Canonicalizer

Md Ashiqur Rahman, Chiao-An Yang, Michael N. Cheng +4

Scale variation is a fundamental challenge in computer vision. Objects of the same class can have different sizes, and their perceived size is further affected by the distance from…

cs.LG2025

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…

cs.LG2024★ 4 cited

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…

cs.LG2023★ 1 cited

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…