3 papers
cs.LG2026
Supervised Distributional Reduction via Optimal Transport and Dependence Maximization
Sai-Aakash Ramesh, Archit Sood, Andrew Corbett +1
Learning representations that capture both intrinsic data geometry and target-relevant structure remains a fundamental challenge, particularly in settings where data reduction must…
cs.AI2026
Boosting Inference with Guided Reasoning: Stochastic Exploration for Recursive Models
Andrew Corbett, Archit Sood, Anna Tzatzopoulou +2
Recent work on recursive architectures has shown that tiny neural networks can be surprisingly powerful on structured reasoning tasks. The trick is to model reasoning trajectories…
cs.MS2024
Democratizing Uncertainty Quantification
Linus Seelinger, Anne Reinarz, Mikkel B. Lykkegaard +22
Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In thi…