6 papers
FLARE: Fast Low-rank Attention Routing Engine
Vedant Puri, Aditya Joglekar, Sri Datta Ganesh Bandreddi +4
The quadratic complexity of self-attention limits the scalability of transformers on long sequences. We introduce Fast Low-rank Attention Routing Engine (FLARE), a token-mixing ope…
Attention to Detail: Fine-Scale Feature Preservation-Oriented Geometric Pre-training for AI-Driven Surrogate Modeling
Yu-hsuan Chen, Jing Bi, Cyril Ngo Ngoc +3
AI-driven surrogate modeling has become an increasingly effective alternative to physics-based simulations for 3D design, analysis, and manufacturing. These models leverage data-dr…
MDDM: A Molecular Dynamics Diffusion Model to Predict Particle Self-Assembly
Kevin Ferguson, Yu-hsuan Chen, Levent Burak Kara
The discovery and study of new material systems rely on molecular simulations that often come with significant computational expense. We propose MDDM, a Molecular Dynamics Diffusio…
Topology-Agnostic Graph U-Nets for Scalar Field Prediction on Unstructured Meshes
Kevin Ferguson, Yu-hsuan Chen, Yiming Chen +3
Machine-learned surrogate models to accelerate lengthy computer simulations are becoming increasingly important as engineers look to streamline the product design cycle. In many ca…
VIRL: Volume-Informed Representation Learning towards Few-shot Manufacturability Estimation
Yu-hsuan Chen, Jonathan Cagan, Levent Burak kara
Designing for manufacturing poses significant challenges in part due to the computation bottleneck of Computer-Aided Manufacturing (CAM) simulations. Although deep learning as an a…
Curve-based Neural Style Transfer
Yu-hsuan Chen, Levent Burak Kara, Jonathan Cagan
This research presents a new parametric style transfer framework specifically designed for curve-based design sketches. In this research, traditional challenges faced by neural sty…