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Adaptive noisy importance sampling for stochastic optimization., , and . CAMSAP, page 1-5. IEEE, (2017)VarGrad: A Low-Variance Gradient Estimator for Variational Inference., , , , and . NeurIPS, (2020)The Incremental Proximal Method: A Probabilistic Perspective., , and . ICASSP, page 4279-4283. IEEE, (2018)Efficient Prior Calibration From Indirect Data., , , and . CoRR, (2024)Nudging the particle filter., and . Stat. Comput., 30 (2): 305-330 (2020)Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization., and . J. Mach. Learn. Res., (2024)On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates., , , , and . CoRR, (2023)Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs., , , , and . CoRR, (2022)Probabilistic Sequential Matrix Factorization., , , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 3484-3492. PMLR, (2021)A Primer on Variational Inference for Physics-Informed Deep Generative Modelling., , , , and . CoRR, (2024)