Showing 1–20 of 44 results
/ Date/ Name
May 8, 2020Amortized Bayesian Inference for Models of CognitionApr 22, 2020Amortized Bayesian model comparison with evidential deep learningMar 13, 2020BayesFlow: Learning complex stochastic models with invertible neural networksOct 1, 2020OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in GermanyNov 23, 2022Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive ModelsAug 22, 2023Simulation-Based Prior Knowledge Elicitation for Parametric Bayesian ModelsFeb 17, 2023JANA: Jointly Amortized Neural Approximation of Complex Bayesian ModelsJun 28, 2023BayesFlow: Amortized Bayesian Workflows With Neural NetworksNov 17, 2023Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based InferenceJun 5, 2024Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended InvestigationMar 31, 2025Simulations in Statistical WorkflowsSep 6, 2024Amortized Bayesian WorkflowAug 28, 2025Improving the Accuracy of Amortized Model Comparison with Self-ConsistencyDec 17, 2020Measuring QCD Splittings with Invertible NetworksAug 23, 2024Amortized Bayesian Multilevel ModelsNov 24, 2024Expert-elicitation method for non-parametric joint priors using normalizing flowsMay 23, 2025EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering MediaJan 23, 2025Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled DataOct 13, 2022Meta-Uncertainty in Bayesian Model ComparisonMar 17, 2024The Simplex Projection: Lossless Visualization of 4D Compositional Data on a 2D Canvas