3 papers
stat.ME2024
Assumption violations in causal discovery and the robustness of score matching
Francesco Montagna, Atalanti A. Mastakouri, Elias Eulig +5
When domain knowledge is limited and experimentation is restricted by ethical, financial, or time constraints, practitioners turn to observational causal discovery methods to recov…
cs.CV2024
Trust And Balance: Few Trusted Samples Pseudo-Labeling and Temperature Scaled Loss for Effective Source-Free Unsupervised Domain Adaptation
Andrea Maracani, Lorenzo Rosasco, Lorenzo Natale
Deep Neural Networks have significantly impacted many computer vision tasks. However, their effectiveness diminishes when test data distribution (target domain) deviates from the o…
cs.RO2024
Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors
Gabriele M. Caddeo, Andrea Maracani, Paolo D. Alfano +3
In this paper, we address the Sim2Real gap in the field of vision-based tactile sensors for classifying object surfaces. We train a Diffusion Model to bridge this gap using a relat…