DeepExplain
Neural network attribution framework
A framework for understanding how deep neural networks process input data to produce output
A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)
734 stars
37 watching
133 forks
Language: Python
last commit: about 4 years ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 antoniodeluca/dn2a | A toolkit for building and training dynamic neural networks | 463 |
 zampino/exnn | An Elixir framework for building and training evolutive neural networks. | 99 |
 taolei87/rcnn | An implementation of neural network components and optimization methods for text analysis, including rationales for neural predictions. | 355 |
 tensorlayer/dagan | Generates MRI images from compressed data using a deep learning model | 175 |
 ivan-vasilev/neuralnetworks | A Java implementation of deep learning algorithms and neural networks with GPU acceleration | 1,232 |
 jimmy-ren/vcnn_double-bladed | A GPU-enabled vectorized implementation of CNNs for computer vision tasks | 136 |
 guanghan/darknet | An implementation of a neural network framework for computer vision tasks, supporting both CPU and GPU computation. | 243 |
 idsia/brainstorm | A neural network framework designed to make working with neural networks fast and flexible. | 1,303 |
 pluskid/mocha.jl | A deep learning framework for Julia inspired by Caffe, providing an efficient and modular way to train neural networks. | 1,287 |
 hshindo/merlin.jl | A Julia-based framework for building and training neural networks | 144 |
 hagaygarty/mdcnn | A 3D convolutional neural network framework supporting volumetric inputs and various features like dropout and batch normalization. | 52 |
 datacanvasio/hypernets | An automated machine learning framework that simplifies the development of end-to-end AutoML toolkits for various domains. | 266 |
 csinva/hierarchical-dnn-interpretations | Provides an implementation of Hierarchical explanations for Neural Network predictions | 125 |
 titu1994/keras-resnext | An implementation of ResNeXt models in Keras, allowing for efficient deep neural networks for image classification. | 224 |
 swift-ai/neuralnet | A Swift implementation of a fully connected, feed-forward artificial neural network for deep learning and machine learning applications. | 211 |