Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee

15 November 2020

Papers citing "Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee"

30 / 30 papers shown

Title
Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks Eirik Høyheim Lars Skaaret-Lund Solve Sæbø A. Hubin UQCV BDL 98 0 0 13 Mar 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 114 0 0 25 Feb 2025
Variational Bayesian Bow tie Neural Networks with Shrinkage Alisa Sheinkman Sara Wade BDL UQCV 100 0 0 17 Nov 2024
Efficient Model Compression for Bayesian Neural Networks Diptarka Saha Zihe Liu Feng Liang BDL 45 0 0 01 Nov 2024
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning Boning Zhang Dongzhu Liu Osvaldo Simeone Guanchu Wang Dimitrios Pezaros Guangxu Zhu BDL FedML 73 0 0 18 Oct 2024
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 126 4 0 05 Jun 2024
BMRS: Bayesian Model Reduction for Structured Pruning Dustin Wright Christian Igel Raghavendra Selvan BDL MQ 136 1 0 03 Jun 2024
Misclassification bounds for PAC-Bayesian sparse deep learning The Tien Mai UQCV BDL 111 3 0 02 May 2024
Variational Sampling of Temporal Trajectories Jurijs Nazarovs Zhichun Huang Xingjian Zhen Sourav Pal Rudrasis Chakraborty Vikas Singh 39 0 0 18 Mar 2024
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 108 5 0 04 Mar 2024
Training Bayesian Neural Networks with Sparse Subspace Variational Inference Junbo Li Zichen Miao Qiang Qiu Ruqi Zhang BDL UQCV 52 9 0 16 Feb 2024
Bayesian Personalized Federated Learning with Shared and Personalized Uncertainty Representations Hui Chen Hengyu Liu LongBing Cao Tiancheng Zhang FedML 98 3 0 27 Sep 2023
Bayesian sparsification for deep neural networks with Bayesian model reduction Dimitrije Marković K. Friston S. Kiebel BDL UQCV 68 2 0 21 Sep 2023
Personalized Federated Learning via Amortized Bayesian Meta-Learning Shiyu Liu Shaogao Lv Dun Zeng Zenglin Xu Hongya Wang Yue Yu FedML 87 3 0 05 Jul 2023
A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning Minyoung Kim Timothy M. Hospedales BDL 63 0 0 16 Jun 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference Insung Kong Dongyoon Yang Jongjin Lee Ilsang Ohn Gyuseung Baek Yongdai Kim BDL 86 5 0 24 May 2023
FedHB: Hierarchical Bayesian Federated Learning Minyoung Kim Timothy M. Hospedales FedML 71 6 0 08 May 2023
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows Lars Skaaret-Lund G. Storvik A. Hubin BDL UQCV 64 3 0 05 May 2023
Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty A. Hubin G. Storvik BDL UQCV 117 6 0 01 May 2023
Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering Xu Zhang Wenpeng Li Yunfeng Shao Yinchuan Li FedML 89 5 0 08 Mar 2023
Projective Integral Updates for High-Dimensional Variational Inference J. Duersch 71 1 0 20 Jan 2023
Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning Yingchun Wang Song Guo Jingcai Guo Weizhan Zhang Yi Tian Xu Jiewei Zhang Yi Liu 87 17 0 07 Dec 2022
Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants Liyao (Mars) Gao J. Nathan Kutz AI4CE 86 22 0 19 Nov 2022
On the optimization and pruning for Bayesian deep learning X. Ke Yanan Fan BDL UQCV 75 1 0 24 Oct 2022
Personalized Federated Learning via Variational Bayesian Inference Xu Zhang Yinchuan Li Wenpeng Li Kaiyang Guo Yunfeng Shao FedML 102 91 0 16 Jun 2022
Masked Bayesian Neural Networks : Computation and Optimality Insung Kong Dongyoon Yang Jongjin Lee Ilsang Ohn Yongdai Kim TPM 51 1 0 02 Jun 2022
Uncertainty Quantification for nonparametric regression using Empirical Bayesian neural networks Stefan Franssen Botond Szabó BDL UQCV 89 4 0 27 Apr 2022
Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data Jurijs Nazarovs Rudrasis Chakraborty Songwong Tasneeyapant Sathya Ravi Vikas Singh 40 4 0 18 Feb 2022
Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details Sanket Jantre Shrijita Bhattacharya T. Maiti BDL 88 13 0 25 Aug 2021
Bridging Breiman's Brook: From Algorithmic Modeling to Statistical Learning L. Mentch Giles Hooker 54 9 0 23 Feb 2021