keiserlab / rcav
'Robust Semantic Interpretability: Revisiting Concept Activation Vectors' Official Implementation
☆11Updated 4 years ago
Alternatives and similar repositories for rcav:
Users that are interested in rcav are comparing it to the libraries listed below
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆35Updated 2 years ago
- Fine-grained ImageNet annotations☆29Updated 4 years ago
- An implementation of the Residual Flow algorithm for out-of-distribution detection.☆30Updated 2 years ago
- Learning Robust Global Representations by Penalizing Local Predictive Power (NeurIPS 2019))☆18Updated 2 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 4 years ago
- Visual Representation Learning Benchmark for Self-Supervised Models☆35Updated 11 months ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆44Updated 5 years ago
- Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"☆22Updated 3 years ago
- Out-of-distribution generalization benchmarks for image recognition models☆14Updated 4 years ago
- CME: Concept-based Model Extraction☆12Updated 4 years ago
- This repository contains the implementation of Concept Activation Regions, a new framework to explain deep neural networks with human con…☆11Updated 2 years ago
- [TPAMI 2019] The implementation for "Direction Concentration Learning: Enhancing Congruency in Machine Learning"☆23Updated 5 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 3 years ago
- ☆19Updated 4 years ago
- ☆32Updated 3 years ago
- ☆38Updated 3 years ago
- Explaining Image Classifiers by Counterfactual Generation☆28Updated 2 years ago
- Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning☆40Updated 3 years ago
- Official PyTorch implementation for our ICCV 2019 paper - Fooling Network Interpretation in Image Classification☆24Updated 5 years ago
- PyTorch Implementation of CVPR'19 (oral) - Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach☆27Updated 5 years ago
- Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for…☆25Updated 3 years ago
- ☆46Updated 4 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆55Updated 3 years ago
- DISSECT: Disentangled Simultaneous Explanations via Concept Traversals☆11Updated last year
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)☆96Updated 2 years ago
- Concept activation vectors for Keras☆13Updated 2 years ago
- The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper.☆40Updated 2 years ago
- Overlooked Factors in Concept-based Explanations: Dataset Choice, Concept Learnability, and Human Capability (CVPR 2023)☆9Updated 2 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 3 years ago
- Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"☆33Updated 2 years ago