Efficient Online Variational Estimation via Monte Carlo Sampling
Fuente:
arXiv
Saved in:
| Main Authors: | Chagneux, Mathis, Müller, Mathias, Gloaguen, Pierre, Corff, Sylvain Le, Olsson, Jimmy |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Importance sampling for online variational learning
by: Chagneux, Mathis, et al.
Published: (2024)
by: Chagneux, Mathis, et al.
Published: (2024)
Entropic Mirror Monte Carlo
by: Cherradi, Anas, et al.
Published: (2026)
by: Cherradi, Anas, et al.
Published: (2026)
Independent Component Discovery in Temporal Count Data
by: Chaussard, Alexandre, et al.
Published: (2026)
by: Chaussard, Alexandre, et al.
Published: (2026)
Online Variational Sequential Monte Carlo
by: Mastrototaro, Alessandro, et al.
Published: (2023)
by: Mastrototaro, Alessandro, et al.
Published: (2023)
Tree-based variational inference for Poisson log-normal models
by: Chaussard, Alexandre, et al.
Published: (2024)
by: Chaussard, Alexandre, et al.
Published: (2024)
Variance estimation for Sequential Monte Carlo Algorithms: a backward sampling approach
by: idrissi, Yazid Janati El, et al.
Published: (2022)
by: idrissi, Yazid Janati El, et al.
Published: (2022)
Diffusion posterior sampling for simulation-based inference in tall data settings
by: Linhart, Julia, et al.
Published: (2024)
by: Linhart, Julia, et al.
Published: (2024)
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
by: Agrawal, Raj, et al.
Published: (2024)
by: Agrawal, Raj, et al.
Published: (2024)
Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densities
by: Tran, Jimmy Huy, et al.
Published: (2025)
by: Tran, Jimmy Huy, et al.
Published: (2025)
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms
by: Lau, Tim Tsz-Kit, et al.
Published: (2023)
by: Lau, Tim Tsz-Kit, et al.
Published: (2023)
Recursive Learning of Asymptotic Variational Objectives
by: Mastrototaro, Alessandro, et al.
Published: (2024)
by: Mastrototaro, Alessandro, et al.
Published: (2024)
Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance
by: Moufad, Badr, et al.
Published: (2025)
by: Moufad, Badr, et al.
Published: (2025)
Variational quantization for state space models
by: David, Etienne, et al.
Published: (2024)
by: David, Etienne, et al.
Published: (2024)
Gaussian Invariant Markov Chain Monte Carlo
by: Titsias, Michalis K., et al.
Published: (2025)
by: Titsias, Michalis K., et al.
Published: (2025)
Monte Carlo and quasi-Monte Carlo integration for likelihood functions
by: Tang, Yanbo
Published: (2025)
by: Tang, Yanbo
Published: (2025)
Multivariate and Online Transfer Learning with Uncertainty Quantification
by: Hickey, Jimmy, et al.
Published: (2024)
by: Hickey, Jimmy, et al.
Published: (2024)
Randomized Quasi-Monte Carlo Features for Kernel Approximation
by: Huang, Yian, et al.
Published: (2025)
by: Huang, Yian, et al.
Published: (2025)
Briding Diffusion Posterior Sampling and Monte Carlo methods: a survey
by: Janati, Yazid, et al.
Published: (2025)
by: Janati, Yazid, et al.
Published: (2025)
Theoretical Convergence Guarantees for Variational Autoencoders
by: Surendran, Sobihan, et al.
Published: (2024)
by: Surendran, Sobihan, et al.
Published: (2024)
Scalable Monte Carlo for Bayesian Learning
by: Fearnhead, Paul, et al.
Published: (2024)
by: Fearnhead, Paul, et al.
Published: (2024)
Stereographic Markov Chain Monte Carlo
by: Yang, Jun, et al.
Published: (2022)
by: Yang, Jun, et al.
Published: (2022)
Latent Network Estimation and Variable Selection for Compositional Data via Variational EM
by: Osborne, Nathan, et al.
Published: (2020)
by: Osborne, Nathan, et al.
Published: (2020)
Latent Guided Sampling for Combinatorial Optimization
by: Surendran, Sobihan, et al.
Published: (2025)
by: Surendran, Sobihan, et al.
Published: (2025)
Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte Carlo
by: Huijsdens, Hester, et al.
Published: (2024)
by: Huijsdens, Hester, et al.
Published: (2024)
Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo
by: Wang, Yu, et al.
Published: (2026)
by: Wang, Yu, et al.
Published: (2026)
Bayesian penalized empirical likelihood and Markov Chain Monte Carlo sampling
by: Chang, Jinyuan, et al.
Published: (2024)
by: Chang, Jinyuan, et al.
Published: (2024)
Sample-Efficient Omniprediction for Proper Losses
by: Gibbs, Isaac, et al.
Published: (2025)
by: Gibbs, Isaac, et al.
Published: (2025)
Estimating the Number of Components in Finite Mixture Models via Variational Approximation
by: Wang, Chenyang, et al.
Published: (2024)
by: Wang, Chenyang, et al.
Published: (2024)
Markov chain Monte Carlo without evaluating the target: an auxiliary variable approach
by: Yuan, Wei, et al.
Published: (2024)
by: Yuan, Wei, et al.
Published: (2024)
Estimating Bidirectional Causal Effects with Large Scale Online Kernel Learning
by: Tanaka, Masahiro
Published: (2025)
by: Tanaka, Masahiro
Published: (2025)
Statistically Efficient Bayesian Sequential Experiment Design via Reinforcement Learning with Cross-Entropy Estimators
by: Blau, Tom, et al.
Published: (2023)
by: Blau, Tom, et al.
Published: (2023)
Advanced Tutorial: Label-Efficient Two-Sample Tests
by: Li, Weizhi, et al.
Published: (2025)
by: Li, Weizhi, et al.
Published: (2025)
Communication-Efficient Distributed Estimation and Inference for Cox's Model
by: Bayle, Pierre, et al.
Published: (2023)
by: Bayle, Pierre, et al.
Published: (2023)
Monte Carlo inference for semiparametric Bayesian regression
by: Kowal, Daniel R., et al.
Published: (2023)
by: Kowal, Daniel R., et al.
Published: (2023)
Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective
by: Elmachtoub, Adam N., et al.
Published: (2023)
by: Elmachtoub, Adam N., et al.
Published: (2023)
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
by: Llorente, F., et al.
Published: (2021)
by: Llorente, F., et al.
Published: (2021)
Efficient Covariance Estimation for Sparsified Functional Data
by: Zheng, Sijie, et al.
Published: (2025)
by: Zheng, Sijie, et al.
Published: (2025)
PPI is the Difference Estimator: Recognizing the Survey Sampling Roots of Prediction-Powered Inference
by: Mozer, Reagan
Published: (2026)
by: Mozer, Reagan
Published: (2026)
Better Locally Private Sparse Estimation Given Multiple Samples Per User
by: Ma, Yuheng, et al.
Published: (2024)
by: Ma, Yuheng, et al.
Published: (2024)
Modeling Spatio-temporal Extremes via Conditional Variational Autoencoders
by: Ma, Xiaoyu, et al.
Published: (2025)
by: Ma, Xiaoyu, et al.
Published: (2025)
Similar Items
-
Importance sampling for online variational learning
by: Chagneux, Mathis, et al.
Published: (2024) -
Entropic Mirror Monte Carlo
by: Cherradi, Anas, et al.
Published: (2026) -
Independent Component Discovery in Temporal Count Data
by: Chaussard, Alexandre, et al.
Published: (2026) -
Online Variational Sequential Monte Carlo
by: Mastrototaro, Alessandro, et al.
Published: (2023) -
Tree-based variational inference for Poisson log-normal models
by: Chaussard, Alexandre, et al.
Published: (2024)