deel-ai / deel-lipLinks
Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layers
β96Updated 3 months ago
Alternatives and similar repositories for deel-lip
Users that are interested in deel-lip are comparing it to the libraries listed below
Sorting:
- π Influenciae is a Tensorflow Toolbox for Influence Functionsβ63Updated last year
- β37Updated 3 weeks ago
- Build and train Lipschitz-constrained networks: PyTorch implementation of 1-Lipschitz layers. For TensorFlow/Keras implementation, see htβ¦β31Updated last week
- Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.β58Updated this week
- New implementations of old orthogonal layers unlock large scale training.β17Updated 2 weeks ago
- Documentationβ23Updated this week
- π Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)β30Updated 2 years ago
- MetaQuantus is an XAI performance tool to identify reliable evaluation metricsβ35Updated last year
- π Overcomplete is a Vision-based SAE Toolboxβ63Updated 2 months ago
- π CODS - Conformal Object Detection and Segmentationβ14Updated this week
- π Xplique is a Neural Networks Explainability Toolboxβ689Updated 8 months ago
- β13Updated 2 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotligβ¦β150Updated 2 years ago
- π Puncc is a python library for predictive uncertainty quantification using conformal prediction.β333Updated 2 weeks ago
- HCOMP '22 -- Eliciting and Learning with Soft Labels from Every Annotatorβ10Updated 2 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true claβ¦β241Updated 2 years ago
- π Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)β65Updated last year
- The PyExperimenter is a tool for the automatic execution of experiments, e.g. for machine learning (ML), capturing corresponding results β¦β38Updated last month
- Conformal prediction for uncertainty quantification in image segmentationβ23Updated 6 months ago
- Open-source framework for uncertainty and deep learning models in PyTorchβ405Updated last week
- OpenXAI : Towards a Transparent Evaluation of Model Explanationsβ247Updated 10 months ago
- β11Updated 4 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".β112Updated 3 years ago
- Model-agnostic posthoc calibration without distributional assumptionsβ42Updated last year
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertaintyβ142Updated 2 years ago
- Our maintained PFN repository. Come here to train SOTA PFNs.β92Updated 3 weeks ago
- Fast and incremental explanations for online machine learning models. Works best with the river framework.β55Updated 5 months ago
- Launching and monitoring Slurm experiments in Pythonβ18Updated 3 weeks ago
- Utilities to perform Uncertainty Quantification on Keras Modelsβ116Updated last year
- Model Agnostic Counterfactual Explanationsβ87Updated 2 years ago