In this work, we extend diffusion solvers to efficiently handle general noisy (non)linear inverse problems via the approximation of the posterior sampling. Interestingly, the resulting posterior ...

AI poses serious risks to Holocaust memory through denial, distortion and clickbait. AI-literate younger generations may be ...

The area of approximation algorithms is aimed at giving provable guarantees on the performance of heuristics for hard problems. The course will present general techniques (such as convex ...

Pull request by Ben Goodrich for fixing the issue with clang4. New version on it's way to CRAN.

Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. Once a well-suited model is established, it can be thoroughly ...

Abstract: We consider the problem of online sparse linear approximation, where a learner sequentially predicts the best sparse linear approximations of an as yet unobserved sequence of measurements in ...

Andlinger Center for Energy and the Environment, Princeton University, Princeton, New Jersey 08544, United States Department of Chemical and Biological Engineering, Princeton University, Princeton, ...

Transportation Science, Vol. 38, No. 3 (August 2004), pp. 343-356 (14 pages) Bounds and approximate formulae are developed for the average optimum distance of the transportation linear programming ...

Two weeks ago, a modest-looking paper was uploaded to the arXiv preprint server with the unassuming title “On the invariant subspace problem in Hilbert spaces”. The paper is just 13 pages long and its ...

The control of general nonlinear systems is a challenging task in particular for large-scale models as they occur in the semi-discretization of partial differential equations (PDEs) of, say, fluid ...

Abstract: This paper deals with the impact of linear approximations for the unknown nonconvex confidence region of chance-constrained ac optimal power flow problems. Such approximations are required ...