Neural Posterior Estimation

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6 papers in the last four weeks, with none the four weeks before. 0.1% of all new papers.

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Latest papers 19

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Amortized Data Borrowing with Exchangeability-Aware Neural Posterior Estimation
Sep 30, 2026Chin-Hung Huang, JooChul Lee, Huan HeNeural Posterior Estimation Amortized Inference
Department of Mathematics and Statistics Auburn University
NeuroDyn-EEG: An Interpretable Pre-trained Model for EEG Based on Neural Dynamics
Sep 29, 2026Yi Cui, Tong Zhao, Jiaxin Lei +5Electroencephalography Neural Posterior Estimation
Gnosis Neurodynamics Co. Ltd, Room 202, West Area, Building North 1, No. 9 Yard, Shengmingyuan Road, Changping District, Beijing, China · School of Biomedical Engineering, Tsinghua Medicine, Tsinghua University, Beijing, China · University of California, Davis, department of psychology +2
Simulation-Based Quantum System Inference with Neural Posterior Estimation
Sep 28, 2026Hang Zou, Anton Frisk Kockum, Martin Rahm +1Simulation-Based Inference Neural Posterior Estimation
Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, 41296 Gothenburg, Sweden · Department of Microtechnology and Nanoscience, Chalmers University of Technology, 41296 Gothenburg, Sweden · Department of Chemistry and Chemical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden
Prior-Amortized In-Context Bayesian Inference for Generalized Linear Mixed-Effects Models
Sep 21, 2026Alex Kipnis, Marcel Binz, Eric SchulzNeural Posterior Estimation Amortized Inference
Institute for Human-Centered AI, Helmholtz Munich, Germany
MAGNETAR: Multipath-Guided Spatial Posteriors for Transmitter Pose Inference in the Upper Mid-Band
Sep 17, 2026Haozhe Lei, Ruibin Chen, Yuhan Jiang +3Neural Posterior Estimation Wireless Localization
NYU WIRELESS, Tandon School of Engineering, New York University, Brooklyn, NY 11201, USA
Neural Posterior Estimation for Tomographic Weak Lensing Mass Mapping
Sep 7, 2026Tim White, Shreyas Chandrashekaran, Camille Avestruz +2Neural Posterior Estimation Bayesian Inverse Problems
Department of Statistics, University of Michigan · Department of Computer Science and Engineering, University of Michigan · Department of Physics, University of Michigan
Divide-and-Conquer: Towards Generalizable Amortized Bayesian Inference for the Drift Diffusion Model
Aug 4, 2026Yufei Wu, Shanqing Gao, Andreas Voss +1Neural Posterior Estimation Cognitive Modeling
1KU Leuven, Belgium · 2Heidelberg University, Germany
An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning
Jul 23, 2026Maximilian Dax, Theo Heimel, Gilles LouppeSimulation-Based Inference Parameter Estimation
ELLIS Institute Tübingen, Max Planck Institute for Intelligent Systems, Tübingen AI Center, Tübingen, Germany · CP3, Université catholique de Louvain, Louvain-la-Neuve, Belgium · Montefiore Institute, University of Liège, Belgium
Neural Posterior Estimation for Inferring Weak Lensing Shear
Jul 10, 2026Tim White, Dingrui Tao, Camille Avestruz +2Simulation-Based Inference Neural Posterior Estimation
Department of Statistics, University of Michigan · Department of Physics, University of Michigan
Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC
Jun 25, 2026Alina Bazarova, Johann Fredrik Jadebeck, Henrik Zunker +5Markov Chain Monte Carlo Simulation-Based Inference
Forschungszentrum Jülich, Jülich Supercomputing Centre, Jülich, Germany · Helmholtz AI, Germany · Forschungszentrum Jülich, Institute of Bio- and Geosciences, Jülich, Germany +3
SOAP-Bubbles: Structured Weight Uncertainty for Neural Networks
Jun 22, 2026Adrian Robert Minut, Nico Daheim, Marco Miani +3Bayesian Neural Networks Neural Posterior Estimation
Sapienza University of Rome, Rome, Italy · Ubiquitous Knowledge Processing Lab (UKP Lab), Department of Computer Science, Technical University of Darmstadt · Technical University of Denmark, Lyngby, Denmark +3
Conservative neural posterior estimation via distributionally robust training
May 27, 2026William Laplante, Yuga Hikida, Charita Dellaporta +2Simulation-Based Inference Neural Posterior Estimation
Department of Statistical Science, University College London, UK · The Alan Turing Institute, UK · Department of Computer Science, Aalto University, Finland
GenSBI: Generative Methods for Simulation-Based Inference in JAX
May 26, 2026Aurelio AmerioFlow Matching Simulation-Based Inference
Instituto de Física Corpuscular (IFIC) Universitat de València & CSIC València, Spain
Mixed neural posterior estimation for simulators with discrete and continuous parameters
May 13, 2026Jan Boelts, Cornelius Schröder, Jonas Beck +3Simulation-Based Inference Parameter Estimation
appliedAI Institute for Europe · Machine Learning in Science, University of Tübingen · Tübingen AI Center +3
It Just Takes Two: Scaling Amortized Inference to Large Sets
May 8, 2026Antoine Wehenkel, Michael Kagan, Lukas Heinrich +1Neural Posterior Estimation Representation Learning
Apple · SLAC National Accelerator Laboratory · TU München +1
Pre-trained Tabular Foundation Models as Versatile Summary Networks for Neural Posterior Estimation
May 8, 2026Elliot Pickens, Chiraag Gohel, Sidharth SatyaTabular Foundation Models Simulation-Based Inference
University of Pennsylvania · The George Washington University · Brown University
Neural Posterior Estimation of Terrain Parameters from Radar Sounder Data
May 5, 2026Jordy Dal Corso, Annalena Kofler, Marco Cortellazzi +2Simulation-Based Inference Parameter Estimation
University of Trento, Trento, Italy · Max Planck Institute for Intelligent Systems, Tübingen, Germany · Max Planck Institute for Gravitational Physics (Albert Einstein Institute), Potsdam, Germany +1
Multiparameter Uncertainty Mapping in Quantitative Molecular MRI using a Physics-Structured Variational Autoencoder (PS-VAE)
Feb 3, 2026Alex Finkelstein, Ron Moneta, Or Zohar +4Magnetic Resonance Imaging Uncertainty Quantification
School of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel · Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel · School of Biochemistry, Neurobiology, and Biophysics, Tel-Aviv University, Tel-Aviv, Israel +1
Causal Posterior Estimation
May 27, 2025Simon Dirmeier, Antonietta MiraBayesian Inference Simulation-Based Inference
Swiss Data Science Center, ETH Zurich, Switzerland · Università della Svizzera italiana, Switzerland · Insubria University, Italy

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Amortized Data Borrowing with Exchangeability-Aware Neural Posterior Estimation

Chin-Hung Huang, JooChul Lee, Huan He

Department of Mathematics and Statistics Auburn University

Neural Posterior Estimation Amortized Inference Bayesian Inference

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Augmenting small concurrent studies with external or historical cohorts is attractive in drug development, where enrollment is slow, follow-up is expensive, and closely related trial or real-world data are often already available. Bayesian dynamic borrowing (BDB) provides a principled framework for adaptively controlling the influence of external data, but classical implementations often depend on hand-specified priors and MCMC-based inference, which can be computationally expensive and not generalizable. In this work, we study amortized neural posterior estimation (NPE) as a flexible alternative. A single network is pretrained on simulated current/external dataset pairs spanning covariate shift, outcome drift, and joint non-exchangeability, and then returns an approximate posterior for a scalar current-study target in a single forward pass. Through simulation studies, we find that NPE is most useful under outcome drift and joint mismatch: in the harder outcome-drift regimes, it gives up to about five-fold lower absolute bias than the best classical baseline and keeps Type I error close to nominal. After pretraining, posterior summaries are obtained in about 8 ms per dataset, roughly

10^3\times

faster than MCMC-based borrowing baselines in our timing experiment. We further analyze Alzheimer's Disease Neuroimaging Initiative (ADNI) data and show that, when mild cognitive impairment outcomes differ across cohorts, the NPE formulation recovers the later-cohort risk level in this example without claiming greater precision. Code is available at https://github.com/ChinHungScott/NPE-for-Bayesian-Dynamic-Borrowing-MLHC-.

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