erfanhatefi / Pruning-by-eXplaining-in-PyTorch
Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers, Paper accepted at eXCV workshop of ECCV 2024
☆22Updated 4 months ago
Alternatives and similar repositories for Pruning-by-eXplaining-in-PyTorch
Users that are interested in Pruning-by-eXplaining-in-PyTorch are comparing it to the libraries listed below
Sorting:
- Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curv…☆16Updated 2 years ago
- Layer-Wise Relevance Propagation for Large Language Models and Vision Transformers [ICML 2024]☆156Updated last month
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆52Updated 2 years ago
- A toolkit for quantitative evaluation of data attribution methods.☆45Updated last month
- CoSy: Evaluating Textual Explanations☆16Updated 3 months ago
- Prototypical Concept-based Explanations, accepted at SAIAD workshop at CVPR 2024.☆15Updated 2 months ago
- ☆17Updated 2 years ago
- ☆11Updated 3 months ago
- Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…☆33Updated 7 months ago
- 👋 Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)☆62Updated last year
- Benchmark of robust self-supervised learning (RobustSSL) methods & Code for AutoLoRa (ICLR 2024).☆16Updated 10 months ago
- Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.☆14Updated last year
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization☆126Updated 11 months ago
- Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet☆31Updated last year
- [ICLR 23] A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled c…☆98Updated last year
- A list of papers that studies out-of-distribution (OOD) detection and misclassification detection (MisD)☆48Updated last year
- [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…☆67Updated last year
- Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.☆19Updated last year
- Implementing LRP (Layer-wise Relevance Propagation) for a sequence-to-sequence model with GRU layers.☆11Updated last year
- Implementation of Concept-level Debugging of Part-Prototype Networks☆12Updated 2 years ago
- ☆16Updated last year
- Testing a model performance for CIFAR10-C☆34Updated 5 years ago
- Pruning CNN using CNN with toy example☆20Updated 3 years ago
- Repository for PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits, accepted at CVPR 2024 XAI4CV Works…☆14Updated 11 months ago
- Re-thinking Federated Active Learning based on Inter-class Diversity (CVPR 2023)☆32Updated last year
- A pytorch implemention of the Explainable AI work 'Contrastive layerwise relevance propagation (CLRP)'☆17Updated 2 years ago
- Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"☆37Updated 2 years ago
- NeurIPS 2021 | Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information☆33Updated 3 years ago
- ☆31Updated 3 years ago
- An Numpy and PyTorch Implementation of CKA-similarity with CUDA support☆90Updated 4 years ago