sebastian-lapuschkin / lrp_toolbox
The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Python. The Toolbox realizes LRP functionality for the Caffe Deep Learning Framework as an extension of Caffe source code published in 10/2015.
☆331Updated 2 years ago
Alternatives and similar repositories for lrp_toolbox:
Users that are interested in lrp_toolbox are comparing it to the libraries listed below
- ☆100Updated 7 years ago
- Layer-wise Relevance Propagation (LRP) for LSTMs.☆223Updated 4 years ago
- Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers☆98Updated 6 years ago
- A toolbox to iNNvestigate neural networks' predictions!☆1,293Updated last year
- A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…☆746Updated 4 years ago
- Tensorflow 2.1 implementation of LRP for LSTMs☆37Updated 2 years ago
- ☆51Updated 4 years ago
- Detect model's attention☆165Updated 4 years ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆135Updated 4 years ago
- Layerwise Relevance Propagation with Deep Taylor Series in TensorFlow☆71Updated 8 years ago
- Tensorflow tutorial for various Deep Neural Network visualization techniques☆347Updated 4 years ago
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆217Updated 8 months ago
- Public facing deeplift repo☆852Updated 2 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- Towards Automatic Concept-based Explanations☆159Updated 11 months ago
- ☆109Updated 2 years ago
- implements some LRP rules to get explanations for Resnets and Densenet-121, including batchnorm-Conv canonization and tensorbiased layers…☆25Updated last year
- ☆134Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 4 years ago
- Tools for training explainable models using attribution priors.☆123Updated 4 years ago
- Attributing predictions made by the Inception network using the Integrated Gradients method☆618Updated 3 years ago
- PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation☆335Updated 3 years ago
- Implementation of layer-wise relevance propagation.☆8Updated 6 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆594Updated last month
- This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpreta…☆358Updated 2 years ago
- Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).☆972Updated last year
- Network Dissection http://netdissect.csail.mit.edu for quantifying interpretability of deep CNNs.☆447Updated 6 years ago
- Visualizing Deep Neural Network Decisions: Prediction Difference Analysis☆117Updated 7 years ago
- reference implementation for "explanations can be manipulated and geometry is to blame"☆36Updated 2 years ago
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization☆124Updated 9 months ago