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
Distributed Combined Space Partitioning and Network Flow Optimization: an Optimal Transport Approach (Extended Version)
Théo Laurentin, Patrick Coirault, Emmanuel Moulay +2
This paper studies a combined space partitioning and network flow optimization problem, with applications to large-scale power, transportation, or communication systems. In dense w…