2 个仓库
Awesome GitHub RepositoriesWeight Normalization
Wraps linear or convolutional modules to implement weight normalization for faster convergence.
Distinct from Convolutional Weight Standardization: Focuses on normalizing the weights of the layer themselves rather than the standardized distribution of convolutional weights.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Weight Normalization. Refine with filters or upvote what's useful.
Awesome Weight Normalization GitHub Repositories
用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
- flashlight/flashlight
flashlight/flashlight
5,443在 GitHub 上查看Flashlight is a standalone C++ machine learning library and tensor library used for building and training neural networks. It functions as a comprehensive neural network framework and automatic differentiation engine, providing the tools to construct computation graphs and calculate gradients via backpropagation. The project serves as a distributed training framework, utilizing all-reduce operations to synchronize gradients and parameters across multiple compute nodes and devices. It distinguishes itself through deep integration of high-performance tensor manipulation, native device memory in
Provides weight normalization wrappers for linear and convolutional modules to accelerate model convergence.
C++ - kmkolasinski/deep-learning-notes
kmkolasinski/deep-learning-notes
1,348在 GitHub 上查看This repository is an educational collection of implementations and research notes focused on deep learning architectures and optimization techniques. It provides modular code examples designed to demonstrate foundational and advanced concepts in machine learning, ranging from basic neural network structures to complex training strategies. The project distinguishes itself by offering practical implementations of specialized research methods, including capsule-based feature aggregation, gradient direction decoupling, and self-normalizing weight regularization. These materials allow for the stu
Implements weight normalization techniques to maintain statistical distributions and prevent vanishing gradients.
Jupyter Notebook
