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stat.CO2026
Sampling through iterated approximation: Gradient-free and multi-fidelity Bayesian inference via transport
Daniel Sharp, Bart van Bloemen Waanders, Youssef Marzouk
We develop an iterative framework for Bayesian inference problems where the posterior distribution may involve computationally intensive models, intractable gradients, significant…
stat.CO2025
A friendly introduction to triangular transport
Maximilian Ramgraber, Daniel Sharp, Mathieu Le Provost +1
Decision making under uncertainty is a cross-cutting challenge in science and engineering. Most approaches to this challenge employ probabilistic representations of uncertainty. In…