3 papers
cs.AI2026
Decomposing Physician Disagreement in HealthBench
Satya Borgohain, Roy Mariathas
We decompose physician disagreement in the HealthBench medical AI evaluation dataset to understand where variance resides and what observable features can explain it. Rubric identi…
cs.LG2022
Bayesian Neural Network Versus Ex-Post Calibration For Prediction Uncertainty
Satya Borgohain, Klaus Ackermann, Ruben Loaiza-Maya
Probabilistic predictions from neural networks which account for predictive uncertainty during classification is crucial in many real-world and high-impact decision making settings…
cs.LG2021
Creating Powerful and Interpretable Models with Regression Networks
Lachlan O'Neill, Simon Angus, Satya Borgohain +2
As the discipline has evolved, research in machine learning has been focused more and more on creating more powerful neural networks, without regard for the interpretability of the…