March 13, 2024, 4:41 a.m. | Fuseinin Mumuni, Alhassan Mumuni

cs.LG updates on

arXiv:2403.07078v1 Announce Type: new
Abstract: We review current and emerging knowledge-informed and brain-inspired cognitive systems for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or few-short learning. Data-driven deep learning models have achieved remarkable performance and demonstrated capabilities surpassing human experts in many applications. Yet, their inability to exploit domain knowledge leads to serious performance limitations in practical applications. In particular, deep learning systems are exposed to adversarial attacks, which can trick them into making glaringly incorrect decisions. Moreover, …

abstract adversarial artificial artificial intelligence arxiv brain brain-inspired capabilities cognitive cs.lg current data data-driven deep learning explainability explainable artificial intelligence human intelligence knowledge performance prior review robustness survey systems type xai zero-shot

Senior Data Engineer

@ Displate | Warsaw

Junior Data Analyst - ESG Data

@ Institutional Shareholder Services | Mumbai

Intern Data Driven Development in Sensor Fusion for Autonomous Driving (f/m/x)

@ BMW Group | Munich, DE

Senior MLOps Engineer, Machine Learning Platform

@ GetYourGuide | Berlin

Data Engineer, Analytics

@ Meta | Menlo Park, CA

Data Engineer

@ Meta | Menlo Park, CA