{"total":19,"rows":[{"id":"2310.01105","title":"Energy-Guided Continuous Entropic Barycenter Estimation for General Costs","created":"2023-10-02","cited_by_count":12,"area":null},{"id":"2205.07475","title":"MixFlows: principled variational inference via mixed flows","created":"2022-05-16","cited_by_count":11,"area":null},{"id":"2111.02434","title":"Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling","created":"2021-11-03","cited_by_count":9,"area":null},{"id":"2203.02836","title":"Recursive Monte Carlo and Variational Inference with Auxiliary Variables","created":"2022-03-05","cited_by_count":8,"area":null},{"id":"2105.03418","title":"Deep Learning Hamiltonian Monte Carlo","created":"2021-05-07","cited_by_count":7,"area":null},{"id":"2307.09607","title":"Sequential Monte Carlo Learning for Time Series Structure Discovery","created":"2023-07-13","cited_by_count":5,"area":null},{"id":"2302.00564","title":"Automatically Marginalized MCMC in Probabilistic Programming","created":"2023-02-01","cited_by_count":4,"area":null},{"id":"2410.18929","title":"AutoStep: Locally adaptive involutive MCMC","created":"2024-10-24","cited_by_count":4,"area":null},{"id":"2112.01582","title":"LeapfrogLayers: A Trainable Framework for Effective Topological Sampling","created":"2021-12-02","cited_by_count":3,"area":null},{"id":"2308.15613","title":"Mixed Variational Flows for Discrete Variables","created":"2023-08-29","cited_by_count":2,"area":null},{"id":"2211.01100","title":"Nonparametric Involutive Markov Chain Monte Carlo","created":"2022-11-02","cited_by_count":1,"area":null},{"id":"2406.02490","title":"Ai-Sampler: Adversarial Learning of Markov kernels with involutive maps","created":"2024-06-04","cited_by_count":1,"area":null},{"id":"2506.02162","title":"Asymptotically exact variational flows via involutive MCMC kernels","created":"2025-06-02","cited_by_count":1,"area":null},{"id":"2301.01409","title":"Geometric Ergodicity in Modified Variations of Riemannian Manifold and Lagrangian Monte Carlo","created":"2023-01-04","cited_by_count":0,"area":null},{"id":"2406.05242","title":"Markov chain Monte Carlo without evaluating the target: an auxiliary variable approach","created":"2024-06-07","cited_by_count":0,"area":null},{"id":"2408.07875","title":"Incremental Structure Discovery of Classification via Sequential Monte Carlo","created":"2024-08-15","cited_by_count":0,"area":null},{"id":"2506.08756","title":"Bayesian Inverse Physics for Neuro-Symbolic Robot Learning","created":"2025-06-10","cited_by_count":0,"area":null},{"id":"2607.15682","title":"Neural Non-Equilibrium Hamiltonian Monte Carlo for Corrected Boltzmann Sampling","created":"2026-07-17","cited_by_count":0,"area":null},{"id":"2608.08588","title":"LazyHMC: Hamiltonian Monte Carlo Simulation for Lazy, Infinite Dimensional Probabilistic Programs","created":"2026-08-09","cited_by_count":0,"area":null}],"next_cursor":null}