Saved in:
| Main Authors: | Wang, Xi, Geffner, Tomas, Domke, Justin |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2210.07290 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Batch and match: black-box variational inference with a score-based divergence
by: Cai, Diana, et al.
Published: (2024)
by: Cai, Diana, et al.
Published: (2024)
Large Language Bayes
by: Domke, Justin
Published: (2025)
by: Domke, Justin
Published: (2025)
Model-Informed Flows for Bayesian Inference
by: Ko, Joohwan, et al.
Published: (2025)
by: Ko, Joohwan, et al.
Published: (2025)
Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI
by: Agrawal, Abhinav, et al.
Published: (2024)
by: Agrawal, Abhinav, et al.
Published: (2024)
Understanding and mitigating difficulties in posterior predictive evaluation
by: Agrawal, Abhinav, et al.
Published: (2024)
by: Agrawal, Abhinav, et al.
Published: (2024)
Amortized Factor Inference Networks for Posterior Inference
by: Ko, Joohwan, et al.
Published: (2026)
by: Ko, Joohwan, et al.
Published: (2026)
Latent Target Score Matching, with an application to Simulation-Based Inference
by: Ko, Joohwan, et al.
Published: (2026)
by: Ko, Joohwan, et al.
Published: (2026)
Learning Straight Flows by Learning Curved Interpolants
by: Shankar, Shiv, et al.
Published: (2025)
by: Shankar, Shiv, et al.
Published: (2025)
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
by: Lai, Jinlin, et al.
Published: (2024)
by: Lai, Jinlin, et al.
Published: (2024)
Theory and computation for structured variational inference
by: Sheng, Shunan, et al.
Published: (2025)
by: Sheng, Shunan, et al.
Published: (2025)
VIKING: Deep variational inference with stochastic projections
by: Fadel, Samuel G., et al.
Published: (2025)
by: Fadel, Samuel G., et al.
Published: (2025)
Uncertainty-aware data assimilation through variational inference
by: Frion, Anthony, et al.
Published: (2025)
by: Frion, Anthony, et al.
Published: (2025)
A variational inference framework for inverse problems
by: Maestrini, Luca, et al.
Published: (2021)
by: Maestrini, Luca, et al.
Published: (2021)
Statistical inference on black-box generative models in the data kernel perspective space
by: Helm, Hayden, et al.
Published: (2024)
by: Helm, Hayden, et al.
Published: (2024)
Simulation-based stacking
by: Yao, Yuling, et al.
Published: (2023)
by: Yao, Yuling, et al.
Published: (2023)
MixFlows: principled variational inference via mixed flows
by: Xu, Zuheng, et al.
Published: (2022)
by: Xu, Zuheng, et al.
Published: (2022)
Predictive variational inference: Learn the predictively optimal posterior distribution
by: Lai, Jinlin, et al.
Published: (2024)
by: Lai, Jinlin, et al.
Published: (2024)
Neural variational inference for cutting feedback during uncertainty propagation
by: Song, Jiafang, et al.
Published: (2025)
by: Song, Jiafang, et al.
Published: (2025)
Tree-based variational inference for Poisson log-normal models
by: Chaussard, Alexandre, et al.
Published: (2024)
by: Chaussard, Alexandre, et al.
Published: (2024)
SoftCVI: Contrastive variational inference with self-generated soft labels
by: Ward, Daniel, et al.
Published: (2024)
by: Ward, Daniel, et al.
Published: (2024)
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)
Partially factorized variational inference for high-dimensional mixed models
by: Goplerud, Max, et al.
Published: (2023)
by: Goplerud, Max, et al.
Published: (2023)
EigenVI: score-based variational inference with orthogonal function expansions
by: Cai, Diana, et al.
Published: (2024)
by: Cai, Diana, et al.
Published: (2024)
Fisher meets Feynman: score-based variational inference with a product of experts
by: Cai, Diana, et al.
Published: (2025)
by: Cai, Diana, et al.
Published: (2025)
Misspecification-robust amortised simulation-based inference using variational methods
by: O'Callaghan, Matthew, et al.
Published: (2025)
by: O'Callaghan, Matthew, et al.
Published: (2025)
Posterior and variational inference for deep neural networks with heavy-tailed weights
by: Castillo, Ismaël, et al.
Published: (2024)
by: Castillo, Ismaël, et al.
Published: (2024)
Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domains
by: Hofmann, Till, et al.
Published: (2024)
by: Hofmann, Till, et al.
Published: (2024)
Batch, match, and patch: low-rank approximations for score-based variational inference
by: Modi, Chirag, et al.
Published: (2024)
by: Modi, Chirag, et al.
Published: (2024)
DySurv: dynamic deep learning model for survival analysis with conditional variational inference
by: Mesinovic, Munib, et al.
Published: (2023)
by: Mesinovic, Munib, et al.
Published: (2023)
Annealing in variational inference mitigates mode collapse: A theoretical study on Gaussian mixtures
by: Fogliani, Luigi, et al.
Published: (2026)
by: Fogliani, Luigi, et al.
Published: (2026)
State estimations and noise identifications with intermittent corrupted observations via Bayesian variational inference
by: Sun, Peng, et al.
Published: (2026)
by: Sun, Peng, et al.
Published: (2026)
A theoretical perspective on mode collapse in variational inference
by: Soletskyi, Roman, et al.
Published: (2024)
by: Soletskyi, Roman, et al.
Published: (2024)
Towards black-box parameter estimation
by: Lenzi, Amanda, et al.
Published: (2023)
by: Lenzi, Amanda, et al.
Published: (2023)
Advancing calibration for stochastic agent-based models in epidemiology with Stein variational inference and Gaussian process surrogates
by: Robertson, Connor, et al.
Published: (2025)
by: Robertson, Connor, et al.
Published: (2025)
Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography
by: Scholz, Vincent C., et al.
Published: (2024)
by: Scholz, Vincent C., et al.
Published: (2024)
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
by: Jiang, Yiheng, et al.
Published: (2023)
by: Jiang, Yiheng, et al.
Published: (2023)
Independent projections of diffusions: Gradient flows for variational inference and optimal mean field approximations
by: Lacker, Daniel
Published: (2023)
by: Lacker, Daniel
Published: (2023)
Conditional neural control variates for variance reduction in Bayesian inverse problems
by: Siahkoohi, Ali, et al.
Published: (2026)
by: Siahkoohi, Ali, et al.
Published: (2026)
Learning General Policies with Policy Gradient Methods
by: Ståhlberg, Simon, et al.
Published: (2025)
by: Ståhlberg, Simon, et al.
Published: (2025)
Learning More Expressive General Policies for Classical Planning Domains
by: Ståhlberg, Simon, et al.
Published: (2024)
by: Ståhlberg, Simon, et al.
Published: (2024)
Similar Items
-
Batch and match: black-box variational inference with a score-based divergence
by: Cai, Diana, et al.
Published: (2024) -
Large Language Bayes
by: Domke, Justin
Published: (2025) -
Model-Informed Flows for Bayesian Inference
by: Ko, Joohwan, et al.
Published: (2025) -
Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI
by: Agrawal, Abhinav, et al.
Published: (2024) -
Understanding and mitigating difficulties in posterior predictive evaluation
by: Agrawal, Abhinav, et al.
Published: (2024)