hans66hsu / nn_interpretabilityLinks
Pytorch implementation of various neural network interpretability methods
☆119Updated 3 years ago
Alternatives and similar repositories for nn_interpretability
Users that are interested in nn_interpretability are comparing it to the libraries listed below
Sorting:
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆139Updated 4 years ago
- This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpreta…☆385Updated 3 years ago
- Basic LRP implementation in PyTorch☆174Updated last year
- Detect model's attention☆170Updated 5 years ago
- Papers and code of Explainable AI esp. w.r.t. Image classificiation☆225Updated 3 years ago
- A pytorch implementation of interpretable convolutional neural network.☆70Updated 4 years ago
- A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.☆102Updated 3 years ago
- ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021☆108Updated 3 years ago
- ☆122Updated 3 years ago
- The official code of Relevance-CAM☆45Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆164Updated 3 years ago
- implements some LRP rules to get explanations for Resnets and Densenet-121, including batchnorm-Conv canonization and tensorbiased layers…☆26Updated last year
- Domain adaptation made easy. Fully featured, modular, and customizable.☆391Updated 2 years ago
- Official implementation of Score-CAM in PyTorch☆432Updated 3 years ago
- The re-implementation of Smooth Grad-CAM++ with pytorch☆66Updated 6 years ago
- ☆113Updated 3 years ago
- Deep Bayesian Active Learning with Image Data by Gal et al. (ICML 2017)☆46Updated 3 years ago
- Pruning CNN using CNN with toy example☆21Updated 4 years ago
- Full-gradient saliency maps☆212Updated 2 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆58Updated 7 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated 2 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆147Updated 2 years ago
- DTD implement on Imagenet pretrained model☆42Updated 5 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
- Addressing Failure Prediction by Learning Model Confidence☆173Updated 3 years ago
- Quantitative Testing with Concept Activation Vectors in PyTorch☆43Updated 6 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆126Updated 6 years ago
- Confidence-Aware Learning for Deep Neural Networks (ICML2020)☆74Updated 5 years ago
- Visually Explainable VAE☆64Updated 5 years ago
- Official implementation of our paper: Towards Robust and Reproducible Active Learning using Neural Networks, accepted at CVPR 2022.☆69Updated 2 years ago