ResearchTrend.AI
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability

Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability

Qiyiwen Zhang
Zhiqi Bu
Kan Chen
Qi Long
ArXivPDFHTML

Papers citing "Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability"

6 / 6 papers shown
Title
Self-Supervised Pretraining for Differentially Private Learning
Self-Supervised Pretraining for Differentially Private Learning
Arash Asadian
Evan Weidner
Lei Jiang
PICV
27
3
0
14 Jun 2022
Improving Adversarial Robustness for Free with Snapshot Ensemble
Improving Adversarial Robustness for Free with Snapshot Ensemble
Yihao Wang
AAML
UQCV
9
1
0
07 Oct 2021
Variational Bayes In Private Settings (VIPS)
Variational Bayes In Private Settings (VIPS)
Mijung Park
James R. Foulds
Kamalika Chaudhuri
Max Welling
21
42
0
01 Nov 2016
Efficient Per-Example Gradient Computations
Efficient Per-Example Gradient Computations
Ian Goodfellow
186
74
0
07 Oct 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
197
745
0
06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015