2 citations · 2 across the 5 of their papers we have counts for
6 papers
Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision
Hans Olischläger, Svenja Jedhoff, Šimon Kucharský +3
Casting Bayesian inference as a neural network optimization problem targeting an amortized posterior is attractive, as it extends to otherwise intractable statistical models and of…
Approximating Bayesian leave-one-group-out cross-validation
Anna Elisabeth Riha, Svenja Jedhoff, Paul-Christian Bürkner +1
When data are grouped, hierarchical or multilevel models are commonly used to account for group-level variation with group-specific parameters. Leave-one-group-out cross-validation…
BayesFlow 2: Multi-Backend Amortized Bayesian Inference in Python
Lars Kühmichel, Jerry M. Huang, Valentin Pratz +11
Modern Bayesian inference involves a mixture of computational methods for estimating, validating, and drawing conclusions from probabilistic models as part of principled workflows.…
From Mice to Trains: Amortized Bayesian Inference on Graph Data
Svenja Jedhoff, Elizaveta Semenova, Aura Raulo +2
Graphs arise across diverse domains, from biology and chemistry to social and information networks, as well as in transportation and logistics. Inference on graph-structured data r…
Testing Hypotheses regarding Covariance and Correlation matrices with the R package CovCorTest
Paavo Sattler, Svenja Jedhoff
In addition to the commonly analyzed measures of location, dispersion measurements such as variance and correlation provide many valuable information. Consequently, they play a cru…
Efficient Uncertainty Propagation in Bayesian Two-Step Procedures
Svenja Jedhoff, Hadi Kutabi, Anne Meyer +1
Bayesian inference provides a principled framework for probabilistic reasoning. If inference is performed in two steps, uncertainty propagation plays a crucial role in accounting f…