da2so / Interpretable-Explanations-of-Black-Boxes-by-Meaningful-PerturbationLinks
Interpretable Explanations of Black Boxes by Meaningful Perturbation Pytorch
☆12Updated last year
Alternatives and similar repositories for Interpretable-Explanations-of-Black-Boxes-by-Meaningful-Perturbation
Users that are interested in Interpretable-Explanations-of-Black-Boxes-by-Meaningful-Perturbation are comparing it to the libraries listed below
Sorting:
- ☆44Updated 5 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆71Updated 4 years ago
- PyTorch reimplementation of computing Shapley values via Truncated Monte Carlo sampling from "What is your data worth? Equitable Valuatio…☆27Updated 3 years ago
- Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020☆64Updated 4 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated 2 years ago
- Official PyTorch implementation for our ICCV 2019 paper - Fooling Network Interpretation in Image Classification☆24Updated 5 years ago
- [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels☆35Updated 4 years ago
- Code for "Supermasks in Superposition"☆124Updated 2 years ago
- ☆83Updated last year
- Interpretation of Neural Network is Fragile☆36Updated last year
- ZSKD with PyTorch☆31Updated 2 years ago
- Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"☆33Updated 3 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 4 years ago
- 1'st Place approach for CVPR 2020 Continual Learning Challenge☆46Updated 5 years ago
- Implementation of the paper "Shapley Explanation Networks"☆88Updated 4 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆17Updated 4 years ago
- Implementation of MLP (python) and CNN (PyTorch) with Information Plane visualization.☆14Updated 7 years ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆45Updated 5 years ago
- Contains notebooks for the PAR tutorial at CVPR 2021.☆36Updated 4 years ago
- Implementation of the paper Identifying Mislabeled Data using the Area Under the Margin Ranking: https://arxiv.org/pdf/2001.10528v2.pdf☆21Updated 5 years ago
- Codebase for the paper "Adversarial Attacks on Time Series"☆24Updated 6 years ago
- Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent☆46Updated 5 years ago
- (NeurIPS 2019) Deep Model Transferbility from Attribution Maps☆20Updated 6 years ago
- ☆32Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- Official repository for the AAAI-21 paper 'Explainable Models with Consistent Interpretations'☆18Updated 3 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Official Repo for "Efficient task-specific data valuation for nearest neighbor algorithms"☆26Updated 5 years ago
- Official PyTorch implementation of “Flexible Dataset Distillation: Learn Labels Instead of Images”☆42Updated 5 years ago
- A general method for training cost-sensitive robust classifier☆22Updated 6 years ago