3 papers
stat.ML2026
Isotonic Survival Regression: Calibrated Survival Distributions from Deep Cox Models
Anchit Jain, Kevin Zhang, Stephen Bates
Time-to-event data is widespread across the life sciences and engineering, but it is typically encountered together with censoring, which complicates the application of standard ma…
stat.ML2026
Deep Ensembles for Epistemic Uncertainty: A Frequentist Perspective
Anchit Jain, Stephen Bates
Decomposing prediction uncertainty into aleatoric (irreducible) and epistemic (reducible) components is critical for the reliable deployment of machine learning systems. While the…
cs.LG2024
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training
Anchit Jain, Rozhin Nobahari, Aristide Baratin +1
Machine learning systems often acquire biases by leveraging undesired features in the data, impacting accuracy variably across different sub-populations. Current understanding of b…