ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1908.04847
  4. Cited By
Convergence Rates of Variational Inference in Sparse Deep Learning

Convergence Rates of Variational Inference in Sparse Deep Learning

9 August 2019
Badr-Eddine Chérief-Abdellatif
    BDL
ArXivPDFHTML

Papers citing "Convergence Rates of Variational Inference in Sparse Deep Learning"

14 / 14 papers shown
Title
Posterior and variational inference for deep neural networks with heavy-tailed weights
Posterior and variational inference for deep neural networks with heavy-tailed weights
Ismael Castillo
Paul Egels
BDL
65
4
0
05 Jun 2024
Deep Horseshoe Gaussian Processes
Deep Horseshoe Gaussian Processes
Ismael Castillo
Thibault Randrianarisoa
BDL
UQCV
54
5
0
04 Mar 2024
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated
  Learning with Bayesian Inference-Based Adaptive Dropout
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout
Jingjing Xue
Min Liu
Sheng Sun
Yuwei Wang
Hui Jiang
Xue Jiang
34
7
0
14 Jul 2023
Personalized Federated Learning via Amortized Bayesian Meta-Learning
Personalized Federated Learning via Amortized Bayesian Meta-Learning
Shiyu Liu
Shaogao Lv
Dun Zeng
Zenglin Xu
Hongya Wang
Yue Yu
FedML
48
3
0
05 Jul 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its
  Posterior Inference
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference
Insung Kong
Dongyoon Yang
Jongjin Lee
Ilsang Ohn
Gyuseung Baek
Yongdai Kim
BDL
43
4
0
24 May 2023
Variational Inference for Bayesian Neural Networks under Model and
  Parameter Uncertainty
Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty
A. Hubin
G. Storvik
BDL
UQCV
67
6
0
01 May 2023
Federated Learning via Variational Bayesian Inference: Personalization,
  Sparsity and Clustering
Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering
Xu Zhang
Wenpeng Li
Yunfeng Shao
Yinchuan Li
FedML
35
4
0
08 Mar 2023
Personalized Federated Learning via Variational Bayesian Inference
Personalized Federated Learning via Variational Bayesian Inference
Xu Zhang
Yinchuan Li
Wenpeng Li
Kaiyang Guo
Yunfeng Shao
FedML
58
87
0
16 Jun 2022
On the inability of Gaussian process regression to optimally learn
  compositional functions
On the inability of Gaussian process regression to optimally learn compositional functions
M. Giordano
Kolyan Ray
Johannes Schmidt-Hieber
76
13
0
16 May 2022
A PAC-Bayes oracle inequality for sparse neural networks
A PAC-Bayes oracle inequality for sparse neural networks
Maximilian F. Steffen
Mathias Trabs
UQCV
29
2
0
26 Apr 2022
User-friendly introduction to PAC-Bayes bounds
User-friendly introduction to PAC-Bayes bounds
Pierre Alquier
FedML
78
201
0
21 Oct 2021
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy
Badr-Eddine Chérief-Abdellatif
Pierre Alquier
105
73
0
29 Sep 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan
Didrik Nielsen
Voot Tangkaratt
Wu Lin
Y. Gal
Akash Srivastava
ODL
80
268
0
13 Jun 2018
Pac-Bayesian Supervised Classification: The Thermodynamics of
  Statistical Learning
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning
O. Catoni
171
458
0
03 Dec 2007
1