목록AI/AI Paper review (14)

Engineering insight

[NeurIPS-2012] ImageNet Classification with Deep Convolutional Neural Networks

역사적인 논문입니다.AI 시대를 연 논문이라고 해도 과언이 아닌 논문으로, Geoffrey Hinton 교수님 연구실에서 나온 논문입니다.작년 LasVegas AI4에서 제프리힌튼 교수님을 실제로 뵈었는데, 노벨상 수상을 하신 후라 그런지 뭔가 말에 무게감이 더 있어지신듯 했습니다.AI계에 역사를 긋는 GAN, Transformer같은 여러논문들이 있지만, 그 모든 시작에는 이 AlexNet이 있다고 봐도 무방할정도라고 생각합니다. ImageNet Classification with Deep Convolutional Neural NetworksNeurIPS 2012 · Alex Krizhevsky, Ilya Sutskever, Geoffrey E. HintonNeurIPS abstract: https:/..
AI/AI Paper review 2026. 5. 1. 21:21
[NeurIPS-2017] Attention is all you need

https://limitsinx.tistory.com/293 [NIPS-2017] Attention is all you need논문 전문 : https://arxiv.org/abs/1706.03762 [출처] https://doi.org/10.48550/arXiv.1706.03762 ※ The picture and content of this article are from the original paper. This article is more of an intuitive understanding than academic analysis. [논문limitsinx.tistory.com이전에 한번 디테일하게 다룬적이 있지만, 구관이 명관이라 다시한번 재정리해보았습니다.Attention Is All You N..
AI/AI Paper review 2026. 4. 30. 21:13
[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 ..
AI/AI Paper review 2025. 7. 3. 16:16
[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 ..
AI/AI Paper review 2025. 6. 30. 10:59
[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..
AI/AI Paper review 2025. 6. 27. 09:06
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