Code release for Unsupervised Domain Adaptation via Distilled Discriminative Clustering published by Pattern Recognition in 2022

Python code for experiments in paper Classification by Separating Hypersurfaces: An Entropic Approach

Adaptive Entropy-Guided Universal Domain Adaptation (AEG-UDA) introduces a novel approach to address universal domain adaptation challenges, focusing on four specific scenarios (Open-Set Domain Adaptation (ODA), Open Partial Domain Adaptation (OPDA), Closed Domain Adaptation (CDA), and Partial Domain Adaptation (PDA))

A minimal PyTorch implementation of YOLOv3, with support for training, inference and evaluation. An addtional implementation of two Unsupervised Domain Adaptation methods (Direct Entropy Minimization and Fourier Domain Adaptation) integrated in the architecture.

Architecture cognitive modulaire (Lichen-OS v2.1) pour l'orchestration de Méta-Morphes. Système bicaméral optimisant l'entropie cognitive via une hypervision de prompts et des noyaux logiques/créatifs spécialisés.