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https://openreview.net/forum?id=1EV6XonWQx Sample Average Approximation for Black-Box Variational Inference | OpenReview Black-box variational inference (BBVI) is a general-purpose approximate inference approach that converts inference to a stochastic optimization problem.... for black variational inference sample average approximation https://gr.thevariationalbook.com/ The Variational Inference Book - Mastering Generative AI A comprehensive book reviewing generative AI including clear mathematical derivations and intuitive illustrations. variational inference book mastering generative ai https://www.jmlr.org/papers/v26/24-0878.html Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs variational inference uncertainty quantification analysis trade https://jmlr.org/papers/v24/21-0169.html Variational Inference for Deblending Crowded Starfields variational inference crowded starfields https://jmlr.org/papers/v26/24-0878.html Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs variational inference uncertainty quantification analysis trade https://openreview.net/forum?id=PiZtlzMWUj SoftCVI: Contrastive variational inference with self-generated soft labels | OpenReview Estimating a distribution given access to its unnormalized density is pivotal in Bayesian inference, where the posterior is generally known only up to an... variational inference contrastive self generated soft https://arxiv.org/abs/2307.10167 [2307.10167] VITS : Variational Inference Thompson Sampling for contextual bandits Abstract page for arXiv paper 2307.10167: VITS : Variational Inference Thompson Sampling for contextual bandits variational inference thompson sampling vits contextual bandits https://deepai.org/publication/variational-inference-for-learning-representations-of-natural-language-edits Variational Inference for Learning Representations of Natural Language Edits | DeepAI Apr 20, 2020 - 04/20/20 - Document editing has become a pervasive component of production of information, with version control systems enabling edits to be ... variational inference for learning natural language representations edits https://arxiv.org/abs/1107.3765 [1107.3765] Using Variational Inference and MapReduce to Scale Topic Modeling Abstract page for arXiv paper 1107.3765: Using Variational Inference and MapReduce to Scale Topic Modeling variational inference to scale using https://openreview.net/forum?id=AHTz2mTlKk Empirical Bayes Trend Filtering Through a Variational Inference Framework | OpenReview This paper introduces a novel framework for Bayesian trend filtering using an empirical Bayes approach and a variational inference algorithm. Trend filtering... variational inference empirical bayes trend filtering https://jmlr.org/papers/v25/22-1392.html Additive smoothing error in backward variational inference for general state-space models variational inference https://www.kth.se/eecs/kalender/black-box-variational-inference-1.1405442 Black-Box Variational Inference | KTH Mixture Models, Efficient Learning, and Applications black box variational inference kth https://openreview.net/forum?id=5TTV5IZnLL Variational Inference with Gaussian Score Matching | OpenReview Variational inference (VI) is a method to approximate the computationally intractable posterior distributions that arise in Bayesian statistics. Typically, VI... variational inference gaussian score matching openreview https://arxiv.org/abs/1206.5162 [1206.5162] Fast Variational Inference in the Conjugate Exponential Family Abstract page for arXiv paper 1206.5162: Fast Variational Inference in the Conjugate Exponential Family variational inference fast conjugate exponential family https://openreview.net/forum?id=lbLC5OV9GY VISA: Variational Inference with Sequential Sample-Average Approximations | OpenReview We present variational inference with sequential sample-average approximations (VISA), a method for approximate inference in computationally intensive models,... variational inference visa sequential sample average https://openreview.net/forum?id=qnQN4yr6FJz Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion... We are concerned with the problem of distributional prediction with incomplete features: The goal is to estimate the distribution of target variables given... variational inference learning https://openreview.net/forum?id=tvxL1eqPl9Y Nested Variational Inference | OpenReview Variational Inference Framework based on Nested Importance Sampling variational inference nested openreview https://openreview.net/forum?id=fHD76uOB4t Censor Dependent Variational Inference | OpenReview This paper provides a comprehensive analysis of variational inference in latent variable models for survival analysis, emphasizing the distinctive challenges... variational inference censor dependent openreview https://openreview.net/forum?id=thUf6ZBlPp EigenVI: score-based variational inference with orthogonal function expansions | OpenReview We develop EigenVI, an eigenvalue-based approach for black-box variational inference (BBVI). EigenVI constructs its variational approximations from orthogonal... variational inference score based orthogonal function https://openreview.net/forum?id=OMOFmb6ve7 Optimization Guarantees for Square-Root Natural-Gradient Variational Inference | OpenReview Variational inference with natural-gradient descent often shows fast convergence in practice, but its theoretical convergence guarantees have been challenging... square root variational inference optimization guarantees natural https://deepai.org/publication/multi-level-monte-carlo-variational-inference Multi-level Monte Carlo Variational Inference | DeepAI Feb 1, 2019 - 02/01/19 - In many statistics and machine learning frameworks, stochastic optimization with high variance gradients has become an important p... multi level monte carlo variational inference deepai https://openreview.net/forum?id=Sxu7xlUJGx Implicit Variational Inference for High-Dimensional Posteriors | OpenReview In variational inference, the benefits of Bayesian models rely on accurately capturing the true posterior distribution. We propose using neural samplers that... variational inference implicit high dimensional openreview https://openreview.net/forum?id=ake1XpIrDKN Variational Inference for Continuous-Time Switching Dynamical Systems | OpenReview Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or... variational inference dynamical systems continuous time switching https://deepai.org/publication/domain-invariant-feature-alignment-using-variational-inference-for-partial-domain-adaptation Domain-Invariant Feature Alignment Using Variational Inference For Partial Domain Adaptation |... Dec 3, 2022 - 12/03/22 - The standard closed-set domain adaptation approaches seek to mitigate distribution discrepancies between two domains under the con... variational inference domain feature alignment using https://deepai.org/publication/variational-inference-based-dropout-in-recurrent-neural-networks-for-slot-filling-in-spoken-language-understanding Variational Inference-Based Dropout in Recurrent Neural Networks for Slot Filling in Spoken... Aug 23, 2020 - 08/23/20 - This paper proposes to generalize the variational recurrent neural network (RNN) with variational inference (VI)-based dropout reg... recurrent neural networks variational inference https://jmlr.org/papers/v26/24-0894.html Posterior and Variational Inference for Deep Neural Networks with Heavy-Tailed Weights deep neural networks variational inference https://www.unsw.edu.au/science/our-schools/maths/engage-with-us/seminars/2025/Variational-inference-for-hierarchical-models-with-conditional-scale-and-skewness-corrections Variational inference for hierarchical models with conditional scale and skewness corrections variational inference hierarchical models https://openreview.net/forum?id=4XtUj6Uzt3&referrer=%5Bthe%20profile%20of%20Junbo%20Li%5D(%2Fprofile%3Fid%3D~Junbo_Li3) Training Bayesian Neural Networks with Sparse Subspace Variational Inference | OpenReview Bayesian neural networks (BNNs) offer uncertainty quantification but come with the downside of substantially increased training and inference costs. Sparse... neural networks variational inference training bayesian sparse https://deepai.org/publication/variational-inference-with-gaussian-score-matching Variational Inference with Gaussian Score Matching | DeepAI Jul 15, 2023 - 07/15/23 - Variational inference (VI) is a method to approximate the computationally intractable posterior distributions that arise in Bayesi... variational inference gaussian score matching deepai https://www.jmlr.org/papers/v27/24-1057.html Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation variational inference extending mean field https://jmlr.org/papers/v25/22-0514.html Structured Optimal Variational Inference for Dynamic Latent Space Models variational inference latent space structured optimal dynamic https://openreview.net/forum?id=Ohxy3YFsUm Variational Inference with Censored Gaussian Process Regressors | OpenReview We consider the problem of Bayesian inference when some observations have been censored. In censored data, the dependent variable has been clipped, so we only... variational inference censored gaussian process openreview https://openreview.net/forum?id=VCVnhR4x4v¬eId=VCVnhR4x4v Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for... Weight space symmetries in neural network architectures, such as permutation symmetries in MLPs, give rise to Bayesian neural network (BNN) posteriors with... variational inference failures model symmetries permutation https://openreview.net/forum?id=OMOFmb6ve7&referrer=%5Bthe%20profile%20of%20Navish%20Kumar%5D(%2Fprofile%3Fid%3D~Navish_Kumar1) Optimization Guarantees for Square-Root Natural-Gradient Variational Inference | OpenReview Variational inference with natural-gradient descent often shows fast convergence in practice, but its theoretical convergence guarantees have been challenging... square root variational inference optimization guarantees natural https://openreview.net/forum?id=r1l4eQW0Z Kernel Implicit Variational Inference | OpenReview Recent progress in variational inference has paid much attention to the flexibility of variational posteriors. One promising direction is to use implicit... variational inference kernel implicit openreview https://openreview.net/forum?id=YsZQhCJunjl MCMC Variational Inference via Uncorrected Hamiltonian Annealing | OpenReview We introduce a new method combining VI and HMC that yields tighter and differentiable lower bounds on the marginal likelihood. variational inference mcmc via uncorrected hamiltonian https://www.kth.se/en/om/upptack/kalender/disputationer/black-box-variational-inference-1.1405442 Black-Box Variational Inference | KTH Mixture Models, Efficient Learning, and Applications black box variational inference kth https://deepai.org/publication/sampling-free-variational-inference-of-bayesian-neural-nets Sampling-Free Variational Inference of Bayesian Neural Nets | DeepAI May 19, 2018 - 05/19/18 - We propose a new Bayesian Neural Net (BNN) formulation that affords variational inference for which the evidence lower bound (ELBO... variational inference neural nets sampling free bayesian https://openreview.net/forum?id=T4-65DNlDij&referrer=%5Bthe%20profile%20of%20Ifigeneia%20Apostolopoulou%5D(%2Fprofile%3Fid%3D~Ifigeneia_Apostolopoulou1) Deep Attentive Variational Inference | OpenReview Stochastic Variational Inference is a powerful framework for learning large-scale probabilistic latent variable models. However, typical assumptions on the... variational inference deep attentive openreview https://deepai.org/publication/black-box-variational-inference-for-stochastic-differential-equations Black-box Variational Inference for Stochastic Differential Equations | DeepAI Feb 9, 2018 - 02/09/18 - Parameter inference for stochastic differential equations is challenging due to the presence of a latent diffusion process. Workin... black box variational inference differential equations stochastic deepai https://jmlr.org/papers/v21/19-1015.html Convergence of Sparse Variational Inference in Gaussian Processes Regression variational inference gaussian processes convergence sparse regression https://deepai.org/publication/mixed-variational-inference Mixed Variational Inference | DeepAI Jan 15, 2019 - 01/15/19 - The Laplace approximation has been one of the workhorses of Bayesian inference. It often delivers good approximations in practice ... variational inference mixed deepai https://deepai.org/publication/differentially-private-partitioned-variational-inference Differentially private partitioned variational inference | DeepAI Sep 23, 2022 - 09/23/22 - Learning a privacy-preserving model from distributed sensitive data is an increasingly important problem, often formulated in the ... variational inference private partitioned deepai https://openreview.net/forum?id=vlY9GDCCA6 PAVI: Plate-Amortized Variational Inference | OpenReview Given observed data and a probabilistic generative model, Bayesian inference searches for the distribution of the model's parameters that could have yielded... variational inference plate openreview https://openreview.net/forum?id=ghIBaprxsV Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration |... Semi-implicit variational inference (SIVI) has been introduced to expand the analytical variational families by defining expressive semi-implicit distributions... variational inference diffusion model hierarchical semi implicit https://openreview.net/forum?id=TskzCtpMEO Training Bayesian Neural Networks with Sparse Subspace Variational Inference | OpenReview Bayesian neural networks (BNNs) offer uncertainty quantification but come with the downside of substantially increased training and inference costs. Sparse... neural networks variational inference training bayesian sparse https://deepai.org/publication/vifs-an-end-to-end-variational-inference-for-foley-sound-synthesis VIFS: An End-to-End Variational Inference for Foley Sound Synthesis | DeepAI Jun 8, 2023 - 06/08/23 - The goal of DCASE 2023 Challenge Task 7 is to generate various sound clips for Foley sound synthesis (FSS) by variational inference foley sound end https://drive.google.com/file/d/1tHKQJ46V91zzxS99CYfw0jT5z1ZQknt0/view?usp=sharing variational inference in stochastic block models.pdf - Google Drive variational inference stochastic block models pdf https://openreview.net/forum?id=55BcghgicI Differentially private partitioned variational inference | OpenReview Learning a privacy-preserving model from sensitive data which are distributed across multiple devices is an increasingly important problem. The problem is... variational inference private partitioned openreview https://openreview.net/forum?id=9Kf9I2nqCh&referrer=%5Bthe%20profile%20of%20Adil%20Salim%5D(%2Fprofile%3Fid%3D~Adil_Salim2) Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space | OpenReview Variational inference (VI) seeks to approximate a target distribution $\pi$ by an element of a tractable family of distributions. Of key interest in statistics... https://openreview.net/forum?id=DvV_blKLiB4 A Mean-Field Variational Inference Approach to Deep Image Prior for Inverse Problems in Medical... We propose a novel MFVI approach to deep image prior for medical image post-processing and show its effectiveness on different tasks and modalities. https://openreview.net/forum?id=2rBLbNJwBm&referrer=%5Bthe%20profile%20of%20Ola%20R%C3%B8nning%5D(%2Fprofile%3Fid%3D~Ola_R%C3%B8nning1) ELBOing Stein: Variational Bayes with Stein Mixture Inference | OpenReview stein bayes mixture inference openreview https://arxiv.org/abs/1901.05534 [1901.05534] Lagging Inference Networks and Posterior Collapse in Variational Autoencoders Abstract page for arXiv paper 1901.05534: Lagging Inference Networks and Posterior Collapse in Variational Autoencoders lagging inference networks https://jmlr.org/papers/v22/20-653.html Multilevel Monte Carlo Variational Inference monte carlo multilevel inference https://openreview.net/forum?id=ZCWIEDEWZP Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix... Given an intractable target density $p$, variational inference (VI) attempts to find the best approximation $q$ from a tractable family $\mathcal Q$. This is... https://openreview.net/forum?id=SJVmjjR9FX Variational Bayesian Phylogenetic Inference | OpenReview The first variational Bayes formulation of phylogenetic inference, a challenging inference problem over structures with intertwined discrete and continuous... bayesian inference openreview https://openreview.net/forum?id=HJgxTf89vV Learning proposals for sequential importance samplers using reinforced variational inference |... The problem of inferring unobserved values in a partially observed trajectory from a stochastic process can be considered as a structured prediction problem.... learning proposals sequential importance samplers https://arxiv.org/abs/2410.19371v2 [2410.19371v2] Noise-Aware Differentially Private Variational Inference Abstract page for arXiv paper 2410.19371v2: Noise-Aware Differentially Private Variational Inference noise aware private inference https://jmlr.org/papers/v25/22-0327.html A Framework for Improving the Reliability of Black-box Variational Inference black box framework improving https://openreview.net/forum?id=KqhMpsWiz2 Variational Transdimensional Inference | OpenReview The expressiveness of flow-based models combined with stochastic variational inference (SVI) has expanded the application of optimization-based Bayesian... inference openreview https://openreview.net/forum?id=s1WJSRaJuy&referrer=%5Bthe%20profile%20of%20Alexandre%20Bouchard-C%C3%B4t%C3%A9%5D(%2Fprofile%3Fid%3D~Alexandre_Bouchard-C%C3%B4t%C3%A92) Variational Phylogenetic Inference with Products over Bipartitions | OpenReview Bayesian phylogenetics is vital for understanding evolutionary dynamics, and requires accurate and efficient approximation of posterior distributions over... inference products openreview https://www.cwi.nl/en/research/computational-imaging/events/learning-to-sample-practical-variational-bayesian-inference-tristan-van-leeuwen/ Learning to sample: Practical Variational Bayesian Inference - Tristan van Leeuwen bayesian inference learning sample practical tristan