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08/22/2023
Simulation-Based Prior Knowledge Elicitation for Parametric Bayesian Models
A central characteristic of Bayesian statistics is the ability to consis...
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06/28/2023
BayesFlow: Amortized Bayesian Workflows With Neural Networks
Modern Bayesian inference involves a mixture of computational techniques...
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03/17/2023
Finding Competence Regions in Domain Generalization
We propose a "learning to reject" framework to address the problem of si...
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02/17/2023
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models
This work proposes ”jointly amortized neural approximation” (JANA) of in...
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01/27/2023
A Deep Learning Method for Comparing Bayesian Hierarchical Models
Bayesian model comparison (BMC) offers a principled approach for assessi...
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11/23/2022
Neural Superstatistics: A Bayesian Method for Estimating Dynamic Models of Cognition
Mathematical models of cognition are often memoryless and ignore potenti...
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10/13/2022
Meta-Uncertainty in Bayesian Model Comparison
Bayesian model comparison (BMC) offers a principled probabilistic approa...
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09/06/2022
Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy
Probabilistic (Bayesian) modeling has experienced a surge of application...
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12/16/2021
BayesFlow can reliably detect Model Misspecification and Posterior Errors in Amortized Bayesian Inference
Neural density estimators have proven remarkably powerful in performing ...
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10/01/2020
Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks
Mathematical models in epidemiology strive to describe the dynamics and ...
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05/08/2020
Amortized Bayesian Inference for Models of Cognition
As models of cognition grow in complexity and number of parameters, Baye...
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04/22/2020
Amortized Bayesian model comparison with evidential deep learning
Comparing competing mathematical models of complex natural processes is ...
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03/13/2020