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VIRL: Volume-Informed Representation Learning towards Few-shot
  Manufacturability Estimation

VIRL: Volume-Informed Representation Learning towards Few-shot Manufacturability Estimation

18 June 2024
Yu-Hsuan Chen
Jonathan Cagan
L. Kara
ArXivPDFHTML

Papers citing "VIRL: Volume-Informed Representation Learning towards Few-shot Manufacturability Estimation"

5 / 5 papers shown
Title
Attention to Detail: Fine-Scale Feature Preservation-Oriented Geometric Pre-training for AI-Driven Surrogate Modeling
Attention to Detail: Fine-Scale Feature Preservation-Oriented Geometric Pre-training for AI-Driven Surrogate Modeling
Yu-Hsuan Chen
Jing Bi
Cyril Ngo Ngoc
Victor Oancea
Jonathan Cagan
L. Kara
AI4CE
31
0
0
27 Apr 2025
Scalar Field Prediction on Meshes Using Interpolated Multi-Resolution
  Convolutional Neural Networks
Scalar Field Prediction on Meshes Using Interpolated Multi-Resolution Convolutional Neural Networks
Kevin Ferguson
Andrew Gillman
James Hardin
Levent Burak Kara
AI4CE
28
1
0
07 Oct 2024
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment
  Anything Model
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Zihan Zhong
Zhiqiang Tang
Tong He
Haoyang Fang
Chun Yuan
51
43
0
31 Jan 2024
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
322
7,481
0
11 Nov 2021
The Power of Scale for Parameter-Efficient Prompt Tuning
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
280
3,872
0
18 Apr 2021
1