12 citations · 39 across the 16 of their papers we have counts for
5 papers · 2 filters
Consistency Models for Scalable and Fast Simulation-Based Inference
Marvin Schmitt, Valentin Pratz, Ullrich Köthe +2
Simulation-based inference (SBI) is constantly in search of more expressive and efficient algorithms to accurately infer the parameters of complex simulation models. In line with t…
Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based Inference
Marvin Schmitt, Leona Odole, Stefan T. Radev +1
We present multimodal neural posterior estimation (MultiNPE), a method to integrate heterogeneous data from different sources in simulation-based inference with neural networks. In…
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
Marvin Schmitt, Desi R. Ivanova, Daniel Habermann +3
We propose a method to improve the efficiency and accuracy of amortized Bayesian inference by leveraging universal symmetries in the joint probabilistic model of parameters and dat…
BayesFlow: Amortized Bayesian Workflows With Neural Networks
Stefan T Radev, Marvin Schmitt, Lukas Schumacher +5
Modern Bayesian inference involves a mixture of computational techniques for estimating, validating, and drawing conclusions from probabilistic models as part of principled workflo…
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models
Stefan T. Radev, Marvin Schmitt, Valentin Pratz +3
This work proposes ``jointly amortized neural approximation'' (JANA) of intractable likelihood functions and posterior densities arising in Bayesian surrogate modeling and simulati…