AI RESEARCH
Probabilistic Tree Inference Enabled by FDSOI Ferroelectric FETs
arXiv CS.LG
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ArXi:2604.05115v1 Announce Type: cross Artificial intelligence applications in autonomous driving, medical diagnostics, and financial systems increasingly demand machine learning models that can provide robust uncertainty quantification, interpretability, and noise resilience. Bayesian decision trees (BDTs) are attractive for these tasks because they combine probabilistic reasoning, interpretable decision-making, and robustness to noise.