{"total":27,"rows":[{"id":"2102.07501","title":"Annealed Flow Transport Monte Carlo","created":"2021-02-15","cited_by_count":90,"area":null},{"id":"2201.13117","title":"Continual Repeated Annealed Flow Transport Monte Carlo","created":"2022-01-31","cited_by_count":66,"area":null},{"id":"2208.07698","title":"Score-Based Diffusion meets Annealed Importance Sampling","created":"2022-08-16","cited_by_count":51,"area":null},{"id":"2412.07081","title":"Sequential Controlled Langevin Diffusions","created":"2024-12-10","cited_by_count":48,"area":null},{"id":"2206.04642","title":"Probability flow solution of the Fokker-Planck equation","created":"2022-06-09","cited_by_count":47,"area":null},{"id":"2310.11914","title":"A connection between Tempering and Entropic Mirror Descent","created":"2023-10-18","cited_by_count":16,"area":null},{"id":"2310.03902","title":"Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond","created":"2023-10-05","cited_by_count":13,"area":null},{"id":"2402.07868","title":"Nesting Particle Filters for Experimental Design in Dynamical Systems","created":"2024-02-12","cited_by_count":12,"area":null},{"id":"2410.09697","title":"Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics","created":"2024-10-13","cited_by_count":10,"area":null},{"id":"2412.00200","title":"Scaling of Stochastic Normalizing Flows in $\\mathrm{SU}(3)$ lattice gauge theory","created":"2024-11-29","cited_by_count":10,"area":null},{"id":"2402.16408","title":"Stable Training of Normalizing Flows for High-dimensional Variational Inference","created":"2024-02-26","cited_by_count":6,"area":null},{"id":"2510.25704","title":"Scaling flow-based approaches for topology sampling in $\\mathrm{SU}(3)$ gauge theory","created":"2025-10-29","cited_by_count":6,"area":null},{"id":"2402.07160","title":"PASOA- PArticle baSed Bayesian Optimal Adaptive design","created":"2024-02-11","cited_by_count":5,"area":null},{"id":"2506.05905","title":"Sequential Monte Carlo approximations of Wasserstein--Fisher--Rao gradient flows","created":"2025-06-06","cited_by_count":5,"area":null},{"id":"2208.12830","title":"Mixtures of Gaussian Process Experts with SMC$^2$","created":"2022-08-26","cited_by_count":3,"area":null},{"id":"2605.15308","title":"SMCEvolve: Principled Scientific Discovery via Sequential Monte Carlo Evolution","created":"2026-05-14","cited_by_count":2,"area":null},{"id":"2402.06173","title":"Comparison of parallel SMC and MCMC for Bayesian deep learning","created":"2024-02-09","cited_by_count":1,"area":null},{"id":"2505.13585","title":"Scalable Bayesian Monte Carlo: fast uncertainty estimation beyond deep ensembles","created":"2025-05-19","cited_by_count":1,"area":null},{"id":"2601.22003","title":"Efficient Stochastic Optimisation via Sequential Monte Carlo","created":"2026-01-29","cited_by_count":1,"area":null},{"id":"2602.21272","title":"Counterdiabatic Hamiltonian Monte Carlo","created":"2026-02-24","cited_by_count":1,"area":null},{"id":"2407.20722","title":"Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo","created":"2024-07-30","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":"2505.03797","title":"Utilising Gradient-Based Proposals Within Sequential Monte Carlo Samplers for Training of Partial Bayesian Neural Networks","created":"2025-05-01","cited_by_count":0,"area":null},{"id":"2511.20413","title":"BOCO: Bayesian Online Contextual Optimization for Decision-Focused Online Learning","created":"2025-11-25","cited_by_count":0,"area":null},{"id":"2604.20301","title":"Properties and limitations of geometric tempering for gradient flow dynamics","created":"2026-04-22","cited_by_count":0,"area":null},{"id":"2604.21456","title":"Tempered Sequential Monte Carlo for Trajectory and Policy Optimization with Differentiable Dynamics","created":"2026-04-23","cited_by_count":0,"area":null},{"id":"2606.06288","title":"Discrete Causal Representations from Heterogeneous Domains: A Bayesian Approach with Social Survey Applications","created":"2026-06-04","cited_by_count":0,"area":null}],"next_cursor":null}