3 papers
cs.LG2026
When Do Learned Blocks Preserve Causal Meaning? Block Identifiability and Constructive Causal Abstractions
Karim Zaghw, Wieland Brendel, Patrik Reizinger
Standard identifiability theory assumes one-dimensional latent factors, but learned representations can encode latent information across multidimensional blocks whose internal coor…
cs.AI2026
Renormalising Generative Models for Active Inference: Foundations, Derivations, and Verification
Karim Zaghw, Andrew Pashea, Marc Pritsch +3
Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and temporal domains remains difficul…
cs.CV2020
An Efficient Language-Independent Multi-Font OCR for Arabic Script
Hussein Osman, Karim Zaghw, Mostafa Hazem +1
Optical Character Recognition (OCR) is the process of extracting digitized text from images of scanned documents. While OCR systems have already matured in many languages, they sti…