Paper Reviews
Paper Reviews
Paper reviews are more than just peer reviews. We aim to first provide a detailed summary of what’s in the paper, followed by an assessment of what impression it left behind, and how it fits with developments that have happened since it was published. We strive to keep the word count of the review less than that of the paper. 🛜
Sitemap
- 2023-11-05: : The transformers paper: Attention is all you need
- 2023-10-01: : The Batch Norm paper: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 2023-08-13: : The Adam paper: Adam: A Method for Stochastic Optimization
- 2023-07-15: : The ResNet paper: Deep Residual Learning for Image Recognition
- 2023-05-06: : The Hopfield Nets paper: Neural networks and physical systems with emergent collective computational abilities
- 2023-04-23: : The AlexNet paper: ImageNet Classification with Deep Convolutional Neural Networks