pytorch-struct
Structured Prediction Library
A PyTorch library implementing differentiable structured prediction algorithms for deep learning applications.
Fast, general, and tested differentiable structured prediction in PyTorch
1k stars
33 watching
93 forks
Language: Jupyter Notebook
last commit: over 3 years ago Related projects:
| Repository | Description | Stars |
|---|---|---|
| | A JavaScript library that provides GPU-accelerated deep learning capabilities with automatic differentiation and neural network layers. | 1,093 |
| | A Python framework for building deep learning models with optimized encoding layers and batch normalization. | 2,044 |
| | An implementation of Deepmind's Visual Interaction Networks using PyTorch to predict future events in physical scenes. | 166 |
| | An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch for word language modeling | 245 |
| | Provides Python wrappers for PyTorch and Lua, enabling developers to use PyTorch's deep learning capabilities from both languages. | 432 |
| | A comprehensive tutorial on deep learning for natural language processing with PyTorch, covering the basics and advancing to linguistic structure prediction. | 1,942 |
| | A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision. | 1,236 |
| | A deep learning framework for handling heterogeneous tabular data with diverse column types | 582 |
| | A PyTorch module that adds differentiable optimization as a layer to neural networks | 517 |
| | A deep learning model implementation of the DeepLab ResNet architecture for image segmentation tasks. | 602 |
| | This is an open source PyTorch library providing tools and models to explain the predictions of deep neural networks for natural language processing tasks. | 19 |
| | Implementations of deep learning architectures using PyTorch for image classification tasks on various datasets. | 112 |
| | An implementation of a deep learning model using PyTorch and depthwise separable convolutions for image classification | 249 |
| | An adaptation of a visualization library for PyTorch to facilitate the interpretation and analysis of deep learning models | 610 |
| | A PyTorch implementation of a deep learning model for learning room layouts from 360 photos and providing tools for layout analysis and data augmentation. | 325 |