airbus / decomonLinks
☆38Updated 2 months ago
Alternatives and similar repositories for decomon
Users that are interested in decomon are comparing it to the libraries listed below
Sorting:
- Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layers☆100Updated 8 months ago
- 👋 Influenciae is a Tensorflow Toolbox for Influence Functions☆64Updated last year
- Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.☆60Updated last month
- New implementations of old orthogonal layers unlock large scale training.☆23Updated 2 months ago
- 🪄 Interpreto is an interpretability toolbox for LLMs☆61Updated last week
- 🐟 CODS - Conformal Object Detection and Segmentation☆19Updated 3 weeks ago
- 👋 Xplique is a Neural Networks Explainability Toolbox☆718Updated last week
- 👋 Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)☆31Updated 3 years ago
- MetaQuantus is an XAI performance tool to identify reliable evaluation metrics☆39Updated last year
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆252Updated 2 years ago
- 👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.☆354Updated 2 weeks ago
- Build and train Lipschitz-constrained networks: PyTorch implementation of 1-Lipschitz layers. For TensorFlow/Keras implementation, see ht…☆35Updated 3 weeks ago
- Reliability diagrams visualize whether a classifier model needs calibration☆161Updated 3 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆630Updated 4 months ago
- Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty i…☆266Updated 2 months ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆447Updated last month
- scikit-activeml: A Comprehensive and User-friendly Active Learning Library☆178Updated last week
- A Library for Uncertainty Quantification.☆920Updated 6 months ago
- [CVPRW 2024] Conformal prediction for uncertainty quantification in image segmentation☆26Updated 11 months ago
- Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning☆204Updated last week
- ☆312Updated 8 months ago
- Utilities to perform Uncertainty Quantification on Keras Models☆119Updated last year
- An interactive framework to visualize and analyze your AutoML process in real-time.☆90Updated last week
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated 2 years ago
- HCOMP '22 -- Eliciting and Learning with Soft Labels from Every Annotator☆10Updated 3 years ago
- Lightweight Hyperparameter Optimization 🚂☆149Updated last year
- Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.☆77Updated this week
- Python package to compute interaction indices that extend the Shapley Value. AISTATS 2023.☆18Updated 2 years ago
- ☆89Updated 6 months ago
- (ICML 2023) Feature learning in deep classifiers through Intermediate Neural Collapse: Accompanying code☆15Updated 2 years ago