{"total":25,"rows":[{"id":"2404.12484","title":"Neural Methods for Amortized Inference","created":"2024-04-18","cited_by_count":39,"area":null},{"id":"2208.12942","title":"Likelihood-Free Parameter Estimation with Neural Bayes Estimators","created":"2022-08-27","cited_by_count":32,"area":null},{"id":"2107.14346","title":"Neural Networks for Parameter Estimation in Intractable Models","created":"2021-07-29","cited_by_count":29,"area":null},{"id":"2205.15680","title":"Simulator-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems","created":"2022-05-31","cited_by_count":15,"area":null},{"id":"2206.02218","title":"Statistical Deep Learning for Spatial and Spatio-Temporal Data","created":"2022-06-05","cited_by_count":15,"area":null},{"id":"2310.02600","title":"Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks","created":"2023-10-04","cited_by_count":13,"area":null},{"id":"2107.03920","title":"Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inference","created":"2021-07-08","cited_by_count":11,"area":null},{"id":"2305.04634","title":"Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods","created":"2023-05-08","cited_by_count":10,"area":null},{"id":"2305.04341","title":"Fast parameter estimation of Generalized Extreme Value distribution using Neural Networks","created":"2023-05-07","cited_by_count":7,"area":null},{"id":"2303.15041","title":"Towards black-box parameter estimation","created":"2023-03-27","cited_by_count":6,"area":null},{"id":"2306.15642","title":"Neural Bayes estimators for censored inference with peaks-over-threshold models","created":"2023-06-27","cited_by_count":6,"area":null},{"id":"2404.10899","title":"Demonstrating the power and flexibility of variational assumptions for amortized neural posterior estimation in environmental applications","created":"2024-04-16","cited_by_count":4,"area":null},{"id":"2506.18508","title":"Theoretical guarantees for neural estimators in parametric statistics","created":"2025-06-23","cited_by_count":2,"area":null},{"id":"2201.09485","title":"Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure Transport","created":"2022-01-24","cited_by_count":1,"area":null},{"id":"2306.11487","title":"Efficient Large-scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks","created":"2023-06-20","cited_by_count":1,"area":null},{"id":"2505.03034","title":"Modeling Spatial Extremes using Non-Gaussian Spatial Autoregressive Models via Convolutional Neural Networks","created":"2025-05-05","cited_by_count":1,"area":null},{"id":"2505.09803","title":"LatticeVision: Image to Image Networks for Modeling Non-Stationary Spatial Data","created":"2025-05-14","cited_by_count":1,"area":null},{"id":"2508.02602","title":"Trustworthy scientific inference with generative models","created":"2025-08-04","cited_by_count":1,"area":null},{"id":"2406.14742","title":"Latent Variable Sequence Identification for Cognitive Models with Neural Network Estimators","created":"2024-06-20","cited_by_count":0,"area":null},{"id":"2407.08668","title":"Modeling Spatial Extremal Dependence of Precipitation Using Distributional Neural Networks","created":"2024-07-11","cited_by_count":0,"area":null},{"id":"2411.03620","title":"A Subsampling Based Neural Network for Spatial Data","created":"2024-11-06","cited_by_count":0,"area":null},{"id":"2412.20323","title":"When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer","created":"2024-12-29","cited_by_count":0,"area":null},{"id":"2505.01639","title":"Fast Likelihood-Free Parameter Estimation for L\\'evy Processes","created":"2025-05-03","cited_by_count":0,"area":null},{"id":"2507.12262","title":"A Framework for Nonstationary Gaussian Processes with Neural Network Parameters","created":"2025-07-16","cited_by_count":0,"area":null},{"id":"2605.12118","title":"Keeping Score: Adaptive, Tuning-Free Loss Weighting for Score-Augmented Neural Ratio Estimation","created":"2026-05-12","cited_by_count":0,"area":null}],"next_cursor":null}