fredhohman / summit-notebooks
Notebooks for Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
☆15Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for summit-notebooks
- Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper…☆52Updated this week
- 🏔️ Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations☆112Updated 4 years ago
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆88Updated 3 months ago
- Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations is a ServiceNow Research project that was started at Elemen…☆13Updated last year
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated 7 months ago
- Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023☆72Updated 6 months ago
- For calculating Shapley values via linear regression.☆66Updated 3 years ago
- This repository provides details of the experimental code in the paper: Instance-based Counterfactual Explanations for Time Series Classi…☆18Updated 3 years ago
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆51Updated 2 years ago
- Official repository of ICML 2023 paper: Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat☆23Updated 8 months ago
- This repository contains the implementation of Concept Activation Regions, a new framework to explain deep neural networks with human con…☆9Updated 2 years ago
- Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"☆18Updated 3 years ago
- This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …☆24Updated last year
- Code for "Interpretable image classification with differentiable prototypes assignment", ECCV 2022☆21Updated 2 years ago
- PyTorch reimplementation of computing Shapley values via Truncated Monte Carlo sampling from "What is your data worth? Equitable Valuatio…☆25Updated 2 years ago
- A pytorch implemention of the Explainable AI work 'Contrastive layerwise relevance propagation (CLRP)'☆17Updated 2 years ago
- This is a list of awesome prototype-based papers for explainable artificial intelligence.☆34Updated last year
- ☆27Updated 4 months ago
- NeurIPS 2021 | Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information☆32Updated 2 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆100Updated last year
- An amortized approach for calculating local Shapley value explanations☆92Updated 11 months ago
- A toolkit for quantitative evaluation of data attribution methods.☆33Updated this week
- A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.☆79Updated 2 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated 6 months ago
- Model Zoos published at the NeurIPS 2022 Dataset & Benchmark track: "Model Zoos: A Dataset of Diverse Populations of Neural Network Model…☆54Updated last year
- The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.☆24Updated 3 years ago
- CME: Concept-based Model Extraction☆12Updated 4 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆28Updated 2 years ago
- Implementation of Concept-level Debugging of Part-Prototype Networks☆11Updated last year
- Official code repository for Correct-N-Contrast☆20Updated 2 years ago