AI20 [ICLR-2017] Mode Regularized Generative Adversarial Networks [논문 전문] : https://arxiv.org/abs/1612.02136[출처] https://doi.org/10.48550/arXiv.1612.02136 ※ The picture and content of this article are from the original paper.All picture and figures used in this article are sourced from publicily available on the internet. [논문 요약]Mode Regularized Generative Adversarial Networks MR-GAN은 GAN 초창기에 Mode Collapse 문제를 해결하고자 Mode Seeking GAN과 같이 노이즈와 생성결과물에 대한 명시적인 .. 2025. 7. 3. [ICDM-2021] Towards Generating Real-World Time Series Data [논문 전문] : https://onlinelibrary.wiley.com/doi/abs/10.1002/er.7013[출처] https://arxiv.org/abs/2111.08386 ※ The picture and content of this article are from the original paper.All picture and figures used in this article are sourced from publicily available on the internet. [논문 요약]Towards Generating Real-World Time Series Data Microsoft와 UIUC에서 나온 RTS-GAN이라는 논문입니다.데이터의 퀄리티에 집중하는것 보다는, 실제 데이터에서 있는 .. 2025. 6. 30. [Energy Research-2021] A generative adversarial network based synthetic data augmentation technique for battery condition evaluation [논문 전문] : https://onlinelibrary.wiley.com/doi/abs/10.1002/er.7013[출처] Naaz, Falak & Herle, Aniruddh & Channegowda, Janamejaya & Raj, Aditya & Lakshminarayanan, Meenakshi. (2021). A generative adversarial network‐based synthetic data augmentation technique for battery condition evaluation. International Journal of Energy Research. 45. 10.1002/er.7013. ※ The picture and content of this article ar.. 2025. 6. 27. [NIPS-2020] Denoising Diffusin Probabilistic Models 논문 전문 : https://papers.nips.cc/paper_files/paper/2014/hash/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html [출처] https://doi.org/10.48550/arXiv.2006.11239 ※ The picture and content of this article are from the original paper. This article is more of an intuitive understanding than academic analysis. [논문 요약] Denoising Diffusion Probablistic Models 2020년 이후 나온 논문들 중 가장 핫한 AI 모델을 꼽으라면 당연코 Diffusion M.. 2024. 1. 29. [NIPS-2014] Generative Adversarial Nets 논문 전문 : https://papers.nips.cc/paper_files/paper/2014/hash/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html [출처] https://doi.org/10.48550/arXiv.1406.2661 ※ The picture and content of this article are from the original paper. This article is more of an intuitive understanding than academic analysis. [논문 요약] Generative Adversarial Nets Citation 68,000이 넘는 슈퍼 논문입니다. 저자들만봐도 모두 한명한명 현재 대가라고 불리는 사람들입니다... 2024. 1. 25. 이전 1 2 3 4 다음
