awesome-repositories.com
Blog
MCP
awesome-repositories.com

Descubre los mejores repositorios open-source con nuestra búsqueda potenciada por IA.

ExplorarBúsquedas curadasAlternativas open-sourceSoftware autohospedableBlogMapa del sitio
ProyectoServidor MCPAcerca deCómo clasificamosPrensa
Aviso legalPrivacidadTérminos
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

1 repositorio

Awesome GitHub RepositoriesHierarchical Parameter Optimizations

Traversing nested parameter structures to apply optimizers that support complex model architectures.

Distinct from Layer Parameter Optimization: Distinct from Layer Parameter Optimization: focuses on traversing nested structures for optimization, not reducing layer-level parameter count.

Explore 1 awesome GitHub repository matching artificial intelligence & ml · Hierarchical Parameter Optimizations. Refine with filters or upvote what's useful.

Awesome Hierarchical Parameter Optimizations GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • tensorflow/swiftAvatar de tensorflow

    tensorflow/swift

    6,131Ver en GitHub↗

    Swift for TensorFlow is a custom toolchain that extends the Swift language with first-class automatic differentiation and differentiable types, enabling gradient-based computation directly within the compiler. It integrates the Swift compiler with TensorFlow runtime and XLA backends, allowing tensor operations to be compiled and executed on hardware-accelerated hardware for high-performance machine learning. The project distinguishes itself through compiler-integrated automatic differentiation that computes gradients of user-defined functions and types during compilation, eliminating the need

    Traverses nested parameter structures to apply optimizers for complex model architectures.

    Jupyter Notebook
    Ver en GitHub↗6,131
  1. Home
  2. Artificial Intelligence & ML
  3. Machine Learning
  4. Infrastructure
  5. Optimization & Inference
  6. Training Algorithms
  7. Deep Learning Optimization
  8. Layer Parameter Optimization
  9. Hierarchical Parameter Optimizations