👋 Xplique is a Neural Networks Explainability Toolbox

Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layers

👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.

A runway dataset and a generator of synthetic aerial images with automatic labeling.

Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.

Build and train Lipschitz-constrained networks: PyTorch implementation of 1-Lipschitz layers. For TensorFlow/Keras implementation, see https://github.com/deel-ai/deel-lip

👋 Influenciae is a Tensorflow Toolbox for Influence Functions

Lipdp leverages Lipchitz constraints to train differentially private networks without clipping.

This repository contains the work of Vuong Nguyen that was conducted during his apprenticeship with the DEEL team. Namely, Vuong conducted several experiments to challenge generative data augmentation techniques from a Fairness perspective. He worked under the supervision of Lucas Hervier and Agustin Picard.

👋 Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)