Simulation-Based Inference

Follow this topic Ask about this topic

Momentum

5 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 49

All topics

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
Truncated Neural Likelihood Estimation for Simulation-Based Inference in State-Space Models
May 20, 2026Kostas Tsampourakis, Víctor ElviraSimulation-Based Inference Parameter Estimation
School of Mathematics, University of Edinburgh,, EH9 3FD, U.K.
Theoretical guidelines for annealed Langevin dynamics in compositional simulation-based inference
May 20, 2026Camille Touron, Gabriel V. Cardoso, Julyan Arbel +1Simulation-Based Inference Langevin Dynamics
Univ. Grenoble Alpes, Inria CNRS, Grenoble INP, LJK, France · Geostatistics team, Centre for geosciences and geoengineering Mines Paris, PSL University, Fontaineableau, France
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
Coupling-Informed Transport Maps for Bayesian Filtering in Nonlinear Dynamical Systems
May 13, 2026Dengfei Zeng, Lijian Jiang, Shuyu Sun +1Dynamical Systems Simulation-Based Inference
School of Mathematical Sciences, Tongji University, Shanghai, 200092 China · School of Mathematical Sciences, Tongji University, Shanghai, 200092 China, Key Laboratory of Intelligent Computing and Applications (Ministry of Education), Tongji University, Shanghai, 200092 China
Keeping Score: Adaptive, Tuning-Free Loss Weighting for Score-Augmented Neural Ratio Estimation
May 12, 2026Alexander Shen, Mikael KuuselaNeural Surrogate Modeling Simulation-Based Inference
Department of Statistics and Data Science Carnegie Mellon University Pittsburgh, PA 15213
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
Information-Preserving Domain Transfer with Unlabeled Data in Misspecified Simulation-Based Inference
May 7, 2026Joon Jang, Eunho Jeong, Kyu Sung Choi +1Synthetic-to-Real Domain Adaptation Simulation-Based Inference
Department of Biomedical Sciences, Seoul National University, Seoul, Republic of Korea · Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea · Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea +3
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
Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health
Apr 22, 2026Peter Collett, Alexander Johannes Stasik, Simone Casolo +1Simulation-Based Inference Efficient Inference
Cognite AS, Oslo, Norway · Department of Data Science, Norwegian University of Life Sciences, Ås, Norway · Department for Mathematics and Cybernetics, SINTEF Digital, Oslo, Norway
Tokenised Flow Matching for Hierarchical Simulation Based Inference
Apr 22, 2026Giovanni Charles, Cosmo Santoni, Seth Flaxman +1Flow Matching Simulation-Based Inference
Imperial College London, London, United Kingdom · University of Oxford, Oxford, United Kingdom
Generative Flow Networks for Model Adaptation in Digital Twins of Natural Systems
Apr 22, 2026Pascal Archambault, Houari Sahraoui, Eugene SyrianiSimulation-Based Inference Model Calibration
DIRO, Université de Montréal, Quebec, Canada.
Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference
Apr 20, 2026Jonas Arruda, Sophie Chervet, Paula Staudt +6Simulation-Based Inference Amortized Inference
Bonn Center for Mathematical Life Sciences, University of Bonn, Bonn, Germany · Life & Medical Sciences Institute, University of Bonn, Bonn, Germany · Epidemiology and Modeling of Antibiotic Evasion Unit, Institut Pasteur, Paris, France +12
Diffusion Models in Simulation-Based Inference: A Tutorial Review
Dec 22, 2025Jonas Arruda, Niels Bracher, Ullrich Köthe +2Simulation-Based Inference Parameter Estimation
Bonn Center for Mathematical Life Sciences, Life & Medical Sciences Institute, University of Bonn, Germany · Center for Modeling, Simulation, & Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, NY, USA · Computer Vision and Learning Lab, Heidelberg University, Germany
Posterior-driven Heuristic Support Adaptation in a Probabilistic Treatment of Real2Sim2Real for Vision-Driven Deformable Linear Object Manipulation
Oct 30, 2025Georgios Kamaras, Craig Innes, Subramanian RamamoorthySimulation-Based Inference Adaptive Inference
School of Informatics, The University of Edinburgh, EH8 9AB, UK. · Heriot-Watt University · UKRI Turing AI World Leading Researcher Fellowship on AI for Person-Centred and Teachable Autonomy
Estimating Orbital Parameters of Direct Imaging Exoplanet Using Neural Network
Oct 20, 2025Bo Liang, Hanlin Song, Chang Liu +9Markov Chain Monte Carlo Simulation-Based Inference
Center for Gravitational Wave Experiment, National Microgravity Laboratory, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China · Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou), University of Chinese Academy of Sciences (UCAS), Beijing 100049, China · National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China +6
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
Bifidelity Parameter Estimation Using Conditional Diffusion Models
Apr 2, 2025Caroline Tatsuoka, Minglei Yang, Dongbin Xiu +1Simulation-Based Inference Surrogate Modeling
Department of Mathematics, The Ohio State University, Columbus, OH 43210, USA · Fusion Energy Science Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA · Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA

May 27, 2026, stat.MLJ/K move · Enter open · S save

Conservative neural posterior estimation via distributionally robust training

William Laplante, Yuga Hikida, Charita Dellaporta, François-Xavier Briol+1

Department of Statistical Science, University College London, UK · The Alan Turing Institute, UK · Department of Computer Science, Aalto University, Finland

Simulation-Based Inference Neural Posterior Estimation Probability Calibration Distributionally Robust Optimization Wasserstein Distributionally Robust Optimization Robust Estimation

Open paper AskPDF arXiv

Simulation-based inference with neural posterior estimation (NPE) often yields overconfident and unreliable posteriors under limited simulation budgets. To address this, we propose DRO-NPE, a distributionally robust approach that replaces the standard NPE objective with a worst-case loss over a Wasserstein ambiguity set. We introduce KL-based metrics for miscoverage and miscalibration, and use these to show that the DRO-NPE objective controls overfitting and reduces posterior overconfidence. Our method is tractable, parallelisable, and readily integrates with standard normalising flows. Across benchmark SBI tasks, DRO-NPE consistently improves coverage and calibration, while narrowing the gap between empirical and population NPE loss, leading to more reliable inference in low-simulation regimes.

Momentum

Related topics

Latest papers 49