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목록Optimization (5)
newhaneul
[논문 리뷰] 3D Gaussian Splatting for Real-Time Radiance Field Rendering (ACM Transactions on Graphics, SIGGRAPH 2023)
본 포스팅은 NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (ECCV 2020)을 읽고 정리하기 위한 포스팅입니다.논문명: 3D Gaussian Splatting for Real-Time Radiance Field Rendering (ACM Transactions on Graphics, SIGGRAPH, 2023) 3D Gaussian Splatting for Real-Time Radiance Field RenderingRadiance Field methods have recently revolutionized novel-view synthesis of scenes captured with multiple photos or ..
[Stanford Univ: CS231n] Spring 2025 Assignment1. Q5(Training a fully connected network)
본 포스팅은 Stanford University School of Engineering의 CS231n: Convolutional Neural Networks for Visual Recognition을 수강하고 공부한 내용을 정리하기 위한 포스팅입니다. https://github.com/cs231n/cs231n.github.io/blob/master/assignments/2025/assignment1.md cs231n.github.io/assignments/2025/assignment1.md at master · cs231n/cs231n.github.ioPublic facing notes page. Contribute to cs231n/cs231n.github.io development by creati..
[Stanford Univ: CS231n] Lecture 7. Training Neural Networks Part 2
본 포스팅은 Stanford University School of Engineering의 CS231n: Convolutional Neural Networks for Visual Recognition을 수강하고 공부한 내용을 정리하기 위한 포스팅입니다.https://youtu.be/_JB0AO7QxSA?si=pcEV42NFuWF9os6U https://github.com/cs231n/cs231n.github.io GitHub - cs231n/cs231n.github.io: Public facing notes pagePublic facing notes page. Contribute to cs231n/cs231n.github.io development by creating an account on GitHu..
[Stanford Univ: CS231n] Lecture 3. Loss Functions and Optimization
본 포스팅은 Stanford University School of Engineering의 CS231n: Convolutional Neural Networks for Visual Recognition을 수강하고 공부한 내용을 정리하기 위한 포스팅입니다.https://youtu.be/h7iBpEHGVNc?si=kJoPIdD7yH-Yi-zk https://github.com/cs231n/cs231n.github.io GitHub - cs231n/cs231n.github.io: Public facing notes pagePublic facing notes page. Contribute to cs231n/cs231n.github.io development by creating an account on GitH..
[Seoul National Univ: ML/DL] Lecture 16. Training Neural Networks 2
본 포스팅은 서울대학교 이준석 교수님의 M3239.005300 Machine Learning & Deep Learning 1을 수강하고 공부한 내용을 정리하기 위한 포스팅입니다.이준석 교수님에게 강의 자료 사용에 대한 허락을 받았음을 알립니다.https://youtu.be/IIBCt_g2EW0?si=zdzNoKvHAQyl-n3J 1. Regularization for Neural Networks Overfitting Machien Learning에서 overfitting을 억제하기 위해 Regularization 중 Ridge regression과 Lasso regularization이 있다고 배웠었다. overfitting은 model이 traning data의 nois한 부분까지 학습하게되어 mo..