deel-ai / oodeelLinks
Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.
β59Updated last month
Alternatives and similar repositories for oodeel
Users that are interested in oodeel are comparing it to the libraries listed below
Sorting:
- π Influenciae is a Tensorflow Toolbox for Influence Functionsβ64Updated last year
- Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layersβ98Updated 5 months ago
- β37Updated last month
- New implementations of old orthogonal layers unlock large scale training.β20Updated 2 months ago
- Build and train Lipschitz-constrained networks: PyTorch implementation of 1-Lipschitz layers. For TensorFlow/Keras implementation, see htβ¦β34Updated 2 weeks ago
- Open-source framework for uncertainty and deep learning models in PyTorchβ421Updated last week
- π Xplique is a Neural Networks Explainability Toolboxβ696Updated 10 months ago
- π CODS - Conformal Object Detection and Segmentationβ16Updated last month
- π½ Out-of-Distribution Detection with PyTorchβ308Updated 2 months ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertaintyβ143Updated 2 years ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a β¦β365Updated last year
- [CVPRW 2024] Conformal prediction for uncertainty quantification in image segmentationβ23Updated 8 months ago
- MetaQuantus is an XAI performance tool to identify reliable evaluation metricsβ38Updated last year
- Reliability diagrams visualize whether a classifier model needs calibrationβ155Updated 3 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true claβ¦β244Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".β112Updated 3 years ago
- Inference code for "TabDPT: Scaling Tabular Foundation Models on Real Data"β55Updated last week
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"β272Updated 3 years ago
- πͺ Interpreto is an interpretability toolbox for LLMsβ34Updated last week
- π Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)β30Updated 3 years ago
- NumPy library for calibration metricsβ73Updated 6 months ago
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximizationβ130Updated last year
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"β160Updated last year
- Wasserstein Adversarial Active Learningβ30Updated 5 years ago
- [ICLR2024] Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and Howβ33Updated 9 months ago
- Large-scale uncertainty benchmark in deep learning.β62Updated 3 months ago
- Official PyTorch implementation of improved B-cos modelsβ51Updated last year
- β13Updated 2 years ago
- FFCV-SSL Fast Forward Computer Vision for Self-Supervised Learning.β208Updated 2 years ago
- Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.β77Updated this week