Deep Learning/Review

[논문리뷰] Physics Informed Diffusion Models (PIDM)

작성중입니다... https://arxiv.org/abs/2403.14404 Physics-Informed Diffusion ModelsGenerative models such as denoising diffusion models are quickly advancing their ability to approximate highly complex data distributions. They are also increasingly leveraged in scientific machine learning, where samples from the implied data distributionarxiv.org아이디어: PINN objective를 Diffusion에 통합해서 생성된 데이터가 주어진 물리 (PD..

[논문리뷰] High-Resolution Image Synthesis with Latent Diffusion Models (LDM, Latent Diffusion)

High-Resolution Image Synthesis with Latent Diffusion ModelsBy decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond. Additionally, their formulation allows for a guiding mechanism tarxiv.org내용은 별거 없다. input image의 전체 domain에서 수행하던 diffusion 연산을 latent space에서 한다...

[논문리뷰] U-Net : Convolutional Networks for Biomedical Image Segmentation

대표적인 Semantic segmentation 모델인 U-Net에 대해 알아보자! 원문 링크 : https://arxiv.org/abs/1505.04597 U-Net: Convolutional Networks for Biomedical Image SegmentationThere is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available a..