Imagen de Portada

Large-scale Score-based Variational Posterior Inference for Bayesian Deep Neural Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Kim, Minyoung
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks
por: Gelberg, Yoav, et al.
Publicado: (2024)

Training Bayesian Neural Networks with Sparse Subspace Variational Inference
por: Li, Junbo, et al.
Publicado: (2024)

Robust Bayesian Inference via Variational Approximations of Generalized Rho-Posteriors
por: Khribch, EL Mahdi, et al.
Publicado: (2026)

Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance
por: Loría, Jorge, et al.
Publicado: (2023)

Few-sample Variational Inference of Bayesian Neural Networks with Arbitrary Nonlinearities
por: Schodt, David J.
Publicado: (2024)

On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors
por: Kobialka, Julius, et al.
Publicado: (2026)

Power-scaled Bayesian Inference with Score-based Generative Models
por: Erdinc, Huseyin Tuna, et al.
Publicado: (2025)

A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties
por: Schodt, David J., et al.
Publicado: (2024)

FedHB: Hierarchical Bayesian Federated Learning
por: Kim, Minyoung, et al.
Publicado: (2023)

Towards Improved Variational Inference for Deep Bayesian Models
por: Ober, Sebastian W.
Publicado: (2024)

Conditional Flow Matching for Bayesian Posterior Inference
por: Zhai, Percy S., et al.
Publicado: (2025)

Variational Inference: Posterior Threshold Improves Network Clustering Accuracy in Sparse Regimes
por: Li, Xuezhen, et al.
Publicado: (2023)

Warm-Start Flow Matching for Guaranteed Fast Text/Image Generation
por: Kim, Minyoung
Publicado: (2026)

A Unified Framework for Diffusion Bridge Problems: Flow Matching and Schrödinger Matching into One
por: Kim, Minyoung
Publicado: (2025)

On the Convergence of Locally Adaptive and Scalable Diffusion-Based Sampling Methods for Deep Bayesian Neural Network Posteriors
por: Rensmeyer, Tim, et al.
Publicado: (2024)

Central Limit Theorem for Bayesian Neural Network trained with Variational Inference
por: Descours, Arnaud, et al.
Publicado: (2024)

Quantification of Uncertainties in Probabilistic Deep Neural Network by Implementing Boosting of Variational Inference
por: Bera, Pavia, et al.
Publicado: (2025)

Amortized Factor Inference Networks for Posterior Inference
por: Ko, Joohwan, et al.
Publicado: (2026)

Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks
por: Antoran, Javier
Publicado: (2024)

Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
por: Piriyakulkij, Wasu Top, et al.
Publicado: (2024)

ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems
por: Orozco, Rafael, et al.
Publicado: (2024)

Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian Processes
por: Xu, Jian, et al.
Publicado: (2023)

The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters
por: Koermer, Scott, et al.
Publicado: (2025)

Score-based Generative Neural Networks for Large-Scale Optimal Transport
por: Daniels, Mara, et al.
Publicado: (2021)

A Bayesian Approach to Data Point Selection
por: Xu, Xinnuo, et al.
Publicado: (2024)

Variational Inference on the Final-Layer Output of Neural Networks
por: Wei, Yadi, et al.
Publicado: (2023)

Preconditioned Neural Posterior Estimation for Likelihood-free Inference
por: Wang, Xiaoyu, et al.
Publicado: (2024)

Vector Copula Variational Inference and Dependent Block Posterior Approximations
por: Fu, Yu, et al.
Publicado: (2025)

Posterior Bayesian Neural Networks with Dependent Weights
por: Apollonio, Nicola, et al.
Publicado: (2025)

Free Energy Manifold: Score-Based Inference for Hybrid Bayesian Networks
por: Park, Cheol Young, et al.
Publicado: (2026)

Gibbs Sampling the Posterior of Neural Networks
por: Piccioli, Giovanni, et al.
Publicado: (2023)

Posterior Concentration of Bayesian Physics-Informed Neural Networks for Elliptic PDEs
por: Zhao, Yuxuan, et al.
Publicado: (2026)

A Variational Approach to Bayesian Phylogenetic Inference
por: Zhang, Cheng, et al.
Publicado: (2022)

Rates of Convergence of Generalised Variational Inference Posteriors under Prior Misspecification
por: Mildner, Terje, et al.
Publicado: (2025)

Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks
por: Pilar, Philipp, et al.
Publicado: (2025)

BALI: Learning Neural Networks via Bayesian Layerwise Inference
por: Kurle, Richard, et al.
Publicado: (2024)

Low-Budget Simulation-Based Inference with Bayesian Neural Networks
por: Delaunoy, Arnaud, et al.
Publicado: (2024)

Large Language Models Inference Engines based on Spiking Neural Networks
por: Balaji, Adarsha, et al.
Publicado: (2025)

Variational Stochastic Gradient Descent for Deep Neural Networks
por: Chen, Haotian, et al.
Publicado: (2024)

Variational Learning of Fractional Posteriors
por: Chai, Kian Ming A., et al.
Publicado: (2026)