alewarne / Layerwise-Relevance-Propagation-for-LSTMsLinks
Tensorflow 2.1 implementation of LRP for LSTMs
☆40Updated 3 years ago
Alternatives and similar repositories for Layerwise-Relevance-Propagation-for-LSTMs
Users that are interested in Layerwise-Relevance-Propagation-for-LSTMs are comparing it to the libraries listed below
Sorting:
- Layer-wise Relevance Propagation (LRP) for LSTMs.☆226Updated 5 years ago
- The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Py…☆335Updated 3 years ago
- Explaining Anomalies Detected by Autoencoders Using SHAP☆45Updated 4 years ago
- Adversarial Attacks on Deep Neural Networks for Time Series Classification☆80Updated 5 years ago
- Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification☆98Updated last year
- Pytorch implementation of "Exploring Interpretable LSTM Neural Networks over Multi-Variable Data" https://arxiv.org/pdf/1905.12034.pdf☆110Updated 6 years ago
- Utilities to perform Uncertainty Quantification on Keras Models☆119Updated last year
- ☆30Updated 5 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆85Updated 3 years ago
- ☆91Updated 4 years ago
- TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199☆198Updated 2 years ago
- ☆29Updated 11 months ago
- ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'☆94Updated 5 years ago
- A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…☆760Updated 5 years ago
- DeepStack: Ensembling Keras Deep Learning Models into the next Performance Level☆38Updated 3 years ago
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆238Updated 5 months ago
- XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification☆49Updated 3 years ago
- Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'☆72Updated 4 years ago
- ☆122Updated 3 years ago
- PyTorch based autoencoder for sequential data☆44Updated 5 years ago
- GRU-D, a GRU-based model with trainable decays for multivariate time series classification with missing values/irregular samplings☆138Updated 3 years ago
- RNN and general weights, gradients, & activations visualization in Keras & TensorFlow☆181Updated last year
- Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)☆62Updated 2 years ago
- Critical difference diagram with Wilcoxon-Holm post-hoc analysis.☆299Updated 3 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆636Updated last week
- Counterfactual Explanations for Multivariate Time Series Data☆35Updated last year
- PyTorch implementations of neural networks for timeseries classification☆111Updated 3 years ago
- Explaining Anomalies Detected by Autoencoders Using SHAP☆33Updated 5 years ago
- Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers☆98Updated 7 years ago
- ☆62Updated 4 years ago