2 papers
cs.LG2026
Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler
Yiran Ma, Jerome Le Ny, Zhichao Chen +1
In modern process industries, data-driven models are important tools for real-time monitoring when key performance indicators are difficult to measure directly. While accurate pred…
math.OC2025
An ADMM-Based Approach to Quadratically-Regularized Distributed Optimal Transport on Graphs
Yacine Mokhtari, Emmanuel Moulay, Patrick Coirault +1
Optimal transport on a graph focuses on finding the most efficient way to transfer resources from one distribution to another while considering the graph's structure. This paper in…