Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation

25 March 2021

Papers citing "Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation"

28 / 28 papers shown

Title
TraDE: Transformers for Density Estimation Rasool Fakoor Pratik Chaudhari Jonas W. Mueller Alex Smola 64 30 0 06 Apr 2020
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov Polina Kirichenko Marc Finzi A. Wilson DRL BDL 84 115 0 30 Dec 2019
Deep Learning with Gaussian Differential Privacy Zhiqi Bu Jinshuo Dong Qi Long Weijie J. Su FedML 58 208 0 26 Nov 2019
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 70 46 0 29 Oct 2019
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians Gautam Kamath Or Sheffet Vikrant Singhal Jonathan R. Ullman FedML 61 48 0 09 Sep 2019
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 178 775 0 10 Jun 2019
A General Approach to Adding Differential Privacy to Iterative Training Procedures H. B. McMahan Galen Andrew Ulfar Erlingsson Steve Chien Ilya Mironov Nicolas Papernot Peter Kairouz 67 193 0 15 Dec 2018
Private Selection from Private Candidates Jingcheng Liu Kunal Talwar 61 132 0 19 Nov 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 150 873 0 02 Oct 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu Wang Borja Balle S. Kasiviswanathan 85 398 0 31 Jul 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 295 3,134 0 09 Jul 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 146 442 0 03 Apr 2018
Transformation Autoregressive Networks Junier B. Oliva Kumar Avinava Dubey Manzil Zaheer Barnabás Póczós Ruslan Salakhutdinov Eric Xing J. Schneider OOD 63 86 0 30 Jan 2018
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 210 1,354 0 19 May 2017
Renyi Differential Privacy Ilya Mironov 77 1,259 0 24 Feb 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 213 6,130 0 01 Jul 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 139 1,820 0 15 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 266 3,702 0 26 May 2016
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 84 835 0 06 May 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks Tim Salimans Diederik P. Kingma ODL 194 1,942 0 25 Feb 2016
Differentially Private Analysis of Outliers Rina Okada Kazuto Fukuchi Kazuya Kakizaki Jun Sakuma 36 23 0 24 Jul 2015
MADE: Masked Autoencoder for Distribution Estimation M. Germain Karol Gregor Iain Murray Hugo Larochelle OOD SyDa UQCV 172 868 0 12 Feb 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,305 0 11 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 326 18,625 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 126 2,261 0 30 Oct 2014
Differential Privacy for Functions and Functional Data Rob Hall Alessandro Rinaldo Larry A. Wasserman 84 183 0 12 Mar 2012
Differentially Private Combinatorial Optimization Anupam Gupta Katrina Ligett Frank McSherry Aaron Roth Kunal Talwar 72 231 0 26 Mar 2009