3 papers
cs.RO2026
Simulation-based Learning of Electrical Cabinet Assembly Using Robot Skills
Arik Laemmle, Balázs András Bálint, Philipp Tenbrock +4
This paper presents a simulation-driven approach for automating the force-controlled assembly of electrical terminals on DIN-rails, a task traditionally hindered by high programmin…
cs.LG2025
From Overfitting to Reliability: Introducing the Hierarchical Approximate Bayesian Neural Network
Hayk Amirkhanian, Marco F. Huber
In recent years, neural networks have revolutionized various domains, yet challenges such as hyperparameter tuning and overfitting remain significant hurdles. Bayesian neural netwo…
cs.CL2025
Comparison of Large Language Models for Deployment Requirements
Alper Yaman, Jannik Schwab, Christof Nitsche +2
Large Language Models (LLMs), such as Generative Pre-trained Transformers (GPTs) are revolutionizing the generation of human-like text, producing contextually relevant and syntacti…