{"list":"other","total":52,"rows":[{"id":"1711.01558","title":"Wasserstein Auto-Encoders","created":"2017-11-05","cited_by_count":373},{"id":"1605.09522","title":"Kernel Mean Embedding of Distributions: A Review and Beyond","created":"2016-05-31","cited_by_count":364},{"id":"1505.03906","title":"Training generative neural networks via Maximum Mean Discrepancy optimization","created":"2015-05-14","cited_by_count":151},{"id":"1602.02964","title":"A Kernel Test of Goodness of Fit","created":"2016-02-09","cited_by_count":143},{"id":"1906.04370","title":"Maximum Mean Discrepancy Gradient Flow","created":"2019-06-11","cited_by_count":127},{"id":"1906.00232","title":"Kernel Instrumental Variable Regression","created":"2019-06-01","cited_by_count":118},{"id":"1410.2392","title":"Control functionals for Monte Carlo integration","created":"2014-10-09","cited_by_count":59},{"id":"1906.08283","title":"Minimum Stein Discrepancy Estimators","created":"2019-06-19","cited_by_count":57},{"id":"2105.09994","title":"Kernel Stein Discrepancy Descent","created":"2021-05-20","cited_by_count":57},{"id":"2104.07359","title":"Robust Generalised Bayesian Inference for Intractable Likelihoods","created":"2021-04-15","cited_by_count":53},{"id":"2305.15871","title":"Learning Robust Statistics for Simulation-based Inference under Model Misspecification","created":"2023-05-25","cited_by_count":48},{"id":"2105.05842","title":"Kernel Thinning","created":"2021-05-12","cited_by_count":47},{"id":"1906.05944","title":"Statistical Inference for Generative Models with Maximum Mean Discrepancy","created":"2019-06-13","cited_by_count":45},{"id":"1803.10161","title":"Stein Points","created":"2018-03-27","cited_by_count":43},{"id":"2202.04744","title":"Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap","created":"2022-02-09","cited_by_count":41},{"id":"2305.11463","title":"Generative Sliced MMD Flows with Riesz Kernels","created":"2023-05-19","cited_by_count":37},{"id":"2010.04855","title":"Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves","created":"2020-10-10","cited_by_count":36},{"id":"1909.13339","title":"MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy","created":"2019-09-29","cited_by_count":35},{"id":"1805.08845","title":"Counterfactual Mean Embeddings","created":"2018-05-22","cited_by_count":32},{"id":"2105.03481","title":"Stein's Method Meets Computational Statistics: A Review of Some Recent Developments","created":"2021-05-07","cited_by_count":32},{"id":"1411.0439","title":"Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature","created":"2014-11-03","cited_by_count":31},{"id":"1905.03673","title":"Stein Point Markov Chain Monte Carlo","created":"2019-05-09","cited_by_count":29},{"id":"1906.07832","title":"Kernel quadrature with DPPs","created":"2019-06-18","cited_by_count":27},{"id":"1512.00933","title":"Probabilistic Integration: A Role in Statistical Computation?","created":"2015-12-03","cited_by_count":26},{"id":"1501.02056","title":"Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering","created":"2015-01-09","cited_by_count":22},{"id":"1903.11331","title":"Active Multi-Information Source Bayesian Quadrature","created":"2019-03-27","cited_by_count":17},{"id":"1405.5505","title":"Kernel Mean Shrinkage Estimators","created":"2014-05-21","cited_by_count":16},{"id":"1709.00147","title":"Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings","created":"2017-09-01","cited_by_count":16},{"id":"1801.04153","title":"Bayesian Quadrature for Multiple Related Integrals","created":"2018-01-12","cited_by_count":16},{"id":"2409.14980","title":"(De)-regularized Maximum Mean Discrepancy Gradient Flow","created":"2024-09-23","cited_by_count":16},{"id":"1603.02160","title":"Bayesian Learning of Kernel Embeddings","created":"2016-03-07","cited_by_count":15},{"id":"2109.08944","title":"Vector-Valued Control Variates","created":"2021-09-18","cited_by_count":13},{"id":"2301.11674","title":"Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference","created":"2023-01-27","cited_by_count":13},{"id":"2106.11561","title":"Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo","created":"2021-06-22","cited_by_count":12},{"id":"2502.10600","title":"Weighted quantization using MMD: From mean field to mean shift via gradient flows","created":"2025-02-14","cited_by_count":12},{"id":"1901.03227","title":"Closed-form Expressions for Maximum Mean Discrepancy with Applications to Wasserstein Auto-Encoders","created":"2019-01-10","cited_by_count":11},{"id":"2104.03889","title":"Generalized Bayesian Likelihood-Free Inference","created":"2021-04-08","cited_by_count":11},{"id":"2306.03955","title":"Kernel quadrature with randomly pivoted Cholesky","created":"2023-06-06","cited_by_count":11},{"id":"1804.03016","title":"A Bayes-Sard Cubature Method","created":"2018-04-09","cited_by_count":10},{"id":"2006.07487","title":"Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization","created":"2020-06-12","cited_by_count":10},{"id":"2112.02100","title":"ProbNum: Probabilistic Numerics in Python","created":"2021-12-03","cited_by_count":10},{"id":"2311.13548","title":"Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling","created":"2023-11-22","cited_by_count":10},{"id":"2002.00033","title":"Semi-Exact Control Functionals From Sard's Method","created":"2020-01-31","cited_by_count":9},{"id":"2406.16530","title":"Conditional Bayesian Quadrature","created":"2024-06-24","cited_by_count":9},{"id":"1809.10227","title":"Symmetry Exploits for Bayesian Cubature Methods","created":"2018-09-26","cited_by_count":8},{"id":"1403.7304","title":"Characteristic Kernels and Infinitely Divisible Distributions","created":"2014-03-28","cited_by_count":7},{"id":"2210.06672","title":"Variance-Aware Estimation of Kernel Mean Embedding","created":"2022-10-13","cited_by_count":6},{"id":"2410.22754","title":"An Overview of Causal Inference using Kernel Embeddings","created":"2024-10-30","cited_by_count":6},{"id":"1707.04723","title":"Optimal Monte Carlo integration on closed manifolds","created":"2017-07-15","cited_by_count":5},{"id":"1701.01356","title":"Gaussian Process Quadrature Moment Transform","created":"2017-01-05","cited_by_count":3},{"id":"1409.5178","title":"Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models","created":"2014-09-18","cited_by_count":2},{"id":"2110.09516","title":"Keep it Tighter -- A Story on Analytical Mean Embeddings","created":"2021-10-15","cited_by_count":2}],"next_cursor":null}