Federated Learning for Non-factorizable Models using Deep Generative Prior Approximations
Fuente:
arXiv
Saved in:
| Main Authors: | Hassan, Conor, Bon, Joshua J, Semenova, Elizaveta, Mira, Antonietta, Mengersen, Kerrie |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Scalable Vertical Federated Learning via Data Augmentation and Amortized Inference
by: Hassan, Conor, et al.
Published: (2024)
by: Hassan, Conor, et al.
Published: (2024)
Bayesian score calibration for approximate models
by: Bon, Joshua J, et al.
Published: (2022)
by: Bon, Joshua J, et al.
Published: (2022)
A Principled Approach to Bayesian Transfer Learning
by: Bretherton, Adam, et al.
Published: (2025)
by: Bretherton, Adam, et al.
Published: (2025)
Scale-adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification
by: Di Noia, Antonio, et al.
Published: (2024)
by: Di Noia, Antonio, et al.
Published: (2024)
Bayesian Federated Inference for Survival Models
by: Pazira, Hassan, et al.
Published: (2024)
by: Pazira, Hassan, et al.
Published: (2024)
A general framework for adaptive nonparametric dimensionality reduction
by: Di Noia, Antonio, et al.
Published: (2025)
by: Di Noia, Antonio, et al.
Published: (2025)
BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python
by: Haines, Nathaniel, et al.
Published: (2024)
by: Haines, Nathaniel, et al.
Published: (2024)
DeepVARMA: A Hybrid Deep Learning and VARMA Model for Chemical Industry Index Forecasting
by: Li, Xiang, et al.
Published: (2024)
by: Li, Xiang, et al.
Published: (2024)
Bayesian Federated Inference for estimating Statistical Models based on Non-shared Multicenter Data sets
by: Jonker, Marianne A., et al.
Published: (2023)
by: Jonker, Marianne A., et al.
Published: (2023)
Deep Generative Quantile Bayes
by: Kim, Jungeum, et al.
Published: (2024)
by: Kim, Jungeum, et al.
Published: (2024)
Sequential Adaptive Priors for Orthogonal Functions
by: Sugasawa, Shonosuke, et al.
Published: (2025)
by: Sugasawa, Shonosuke, et al.
Published: (2025)
A Bayesian Non-parametric Approach to Generative Models: Integrating Variational Autoencoder and Generative Adversarial Networks using Wasserstein and Maximum Mean Discrepancy
by: Fazeli-Asl, Forough, et al.
Published: (2023)
by: Fazeli-Asl, Forough, et al.
Published: (2023)
Bayesian Federated Inference for regression models based on non-shared multicenter data sets from heterogeneous populations
by: Jonker, Marianne A, et al.
Published: (2024)
by: Jonker, Marianne A, et al.
Published: (2024)
Scalable Asynchronous Federated Modeling for Spatial Data
by: Shi, Jianwei, et al.
Published: (2025)
by: Shi, Jianwei, et al.
Published: (2025)
Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model
by: Chen, Yujie, et al.
Published: (2025)
by: Chen, Yujie, et al.
Published: (2025)
Temperature Optimization for Bayesian Deep Learning
by: Ng, Kenyon, et al.
Published: (2024)
by: Ng, Kenyon, et al.
Published: (2024)
Generalizing Orthogonalization for Models with Non-Linearities
by: Rügamer, David, et al.
Published: (2024)
by: Rügamer, David, et al.
Published: (2024)
TabMixNN: A Unified Deep Learning Framework for Structural Mixed Effects Modeling on Tabular Data
by: Akdemir, Deniz
Published: (2025)
by: Akdemir, Deniz
Published: (2025)
Spatial Autoregressive Model on a Dirichlet Distribution
by: Nguyen, Teo, et al.
Published: (2024)
by: Nguyen, Teo, et al.
Published: (2024)
Uncertainty Quantification for Prior-Data Fitted Networks using Martingale Posteriors
by: Nagler, Thomas, et al.
Published: (2025)
by: Nagler, Thomas, et al.
Published: (2025)
Non-Negative Stiefel Approximating Flow: Orthogonalish Matrix Optimization for Interpretable Embeddings
by: Avants, Brian B., et al.
Published: (2025)
by: Avants, Brian B., et al.
Published: (2025)
Approximate Bayesian inference for cumulative probit regression models
by: Aliverti, Emanuele
Published: (2025)
by: Aliverti, Emanuele
Published: (2025)
Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm
by: Luo, Nanyu, et al.
Published: (2025)
by: Luo, Nanyu, et al.
Published: (2025)
DeepRV: Accelerating Spatiotemporal Inference with Pre-trained Neural Priors
by: Navott, Jhonathan, et al.
Published: (2025)
by: Navott, Jhonathan, et al.
Published: (2025)
Generative Bayesian Filtering and Parameter Learning
by: Marcelli, Edoardo, et al.
Published: (2025)
by: Marcelli, Edoardo, et al.
Published: (2025)
Redefining the Shortest Path Problem Formulation of the Linear Non-Gaussian Acyclic Model: Pairwise Likelihood Ratios, Prior Knowledge, and Path Enumeration
by: Ong, Hans Jarett J., et al.
Published: (2024)
by: Ong, Hans Jarett J., et al.
Published: (2024)
Distributed Learning of Generalized Linear Causal Networks
by: Ye, Qiaoling, et al.
Published: (2022)
by: Ye, Qiaoling, et al.
Published: (2022)
Neural Generalized Mixed-Effects Models
by: Slavutsky, Yuli, et al.
Published: (2026)
by: Slavutsky, Yuli, et al.
Published: (2026)
Deep Bayes Factors
by: Kim, Jungeum, et al.
Published: (2023)
by: Kim, Jungeum, et al.
Published: (2023)
SSLfmm: An R Package for Semi-Supervised Learning with a Mixed-Missingness Mechanism in Finite Mixture Models
by: McLachlan, Geoffrey J., et al.
Published: (2025)
by: McLachlan, Geoffrey J., et al.
Published: (2025)
Interpretable Network-assisted Random Forest+
by: Tang, Tiffany M., et al.
Published: (2025)
by: Tang, Tiffany M., et al.
Published: (2025)
Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach
by: Cheng, Si, et al.
Published: (2023)
by: Cheng, Si, et al.
Published: (2023)
Bayesian Pliable Lasso with Horseshoe Prior for Interaction Effects in GLMs with Missing Responses
by: Mai, The Tien
Published: (2025)
by: Mai, The Tien
Published: (2025)
Knots and variance ordering of sequential Monte Carlo algorithms
by: Bon, Joshua J, et al.
Published: (2025)
by: Bon, Joshua J, et al.
Published: (2025)
Interventional Time Series Priors for Causal Foundation Models
by: Thumm, Dennis, et al.
Published: (2026)
by: Thumm, Dennis, et al.
Published: (2026)
Identifiable Deep Generative Models via Sparse Decoding
by: Moran, Gemma E., et al.
Published: (2021)
by: Moran, Gemma E., et al.
Published: (2021)
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
by: Wang, Jitao, et al.
Published: (2025)
by: Wang, Jitao, et al.
Published: (2025)
Scalable Bayesian Inference for Generalized Linear Mixed Models via Stochastic Gradient MCMC
by: Berchuck, Samuel I., et al.
Published: (2024)
by: Berchuck, Samuel I., et al.
Published: (2024)
Knowledge Distillation of Uncertainty using Deep Latent Factor Model
by: Park, Sehyun, et al.
Published: (2025)
by: Park, Sehyun, et al.
Published: (2025)
Deep Discrete Encoders: Identifiable Deep Generative Models for Rich Data with Discrete Latent Layers
by: Lee, Seunghyun, et al.
Published: (2025)
by: Lee, Seunghyun, et al.
Published: (2025)
Similar Items
-
Scalable Vertical Federated Learning via Data Augmentation and Amortized Inference
by: Hassan, Conor, et al.
Published: (2024) -
Bayesian score calibration for approximate models
by: Bon, Joshua J, et al.
Published: (2022) -
A Principled Approach to Bayesian Transfer Learning
by: Bretherton, Adam, et al.
Published: (2025) -
Scale-adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification
by: Di Noia, Antonio, et al.
Published: (2024) -
Bayesian Federated Inference for Survival Models
by: Pazira, Hassan, et al.
Published: (2024)