51 citations · 289 across the 43 of their papers we have counts for
49 papers
Statistical inverse learning and -regularization
Abhishake Rastogi, Tatiana A. Bubba, Tapio Helin +1
We study the recovery of sparse functions from finite, noisy, and indirect observations in the framework of statistical inverse learning. The unknown is modeled as an element of $\…
A Convex Approximation Framework for Neural Likelihood-Based Bayesian Inverse Problems
Fabian Schneider, Tapio Helin, Leila Taghizadeh
Many problems in science and engineering are difficult to model accurately, either due to unknown physical mechanisms, poorly quantified measurement uncertainty, or prohibitive com…
Robust Model-Based Iteration for Passive Gamma Emission Tomography
Tommi Heikkilä, Sara Heikkinen, Riina Rimppi +1
Passive Gamma Emission Tomography (PGET) is an International Atomic Energy Agency -approved technique for verifying spent nuclear fuel assemblies prior to geological disposal. Reco…
Batch-based Bayesian Optimal Experimental Design in Linear Inverse Problems
Sofia Mäkinen, Andrew B. Duncan, Tapio Helin
Experimental design is central to science and engineering. A ubiquitous challenge is how to maximize the value of information obtained from expensive or constrained experimental se…
Score-based diffusion models for severely ill-posed problems in diffuse optical tomography
Fabian Schneider, Meghdoot Mozumder, Konstantin Tamarov +4
Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems, enabling high-quality reconstructions in inverse problems by le…
Bayesian optimal experimental design with Wasserstein information criteria
Tapio Helin, Youssef Marzouk, Jose Rodrigo Rojo-Garcia
Bayesian optimal experimental design (OED) provides a principled framework for selecting observations or experiments. We introduce new Bayesian design criteria based on the expecte…