Learning Model Reparametrizations: Implicit Variational Inference by Fitting MCMC distributions

4 August 2017

Papers citing "Learning Model Reparametrizations: Implicit Variational Inference by Fitting MCMC distributions"

17 / 17 papers shown

Title
Learning variational autoencoders via MCMC speed measures Marcel Hirt Vasileios Kreouzis P. Dellaportas BDL DRL 53 2 0 26 Aug 2023
Tensorizing flows: a tool for variational inference Y. Khoo M. Lindsey Renana Keydar DRL 62 4 0 03 May 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 73 14 0 14 Feb 2023
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling Jiri Hron Roman Novak Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 84 7 0 15 Jun 2022
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods Marylou Gabrié Grant M. Rotskoff Eric Vanden-Eijnden 50 21 0 16 Jul 2021
Reparameterized Sampling for Generative Adversarial Networks Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin GAN 59 5 0 01 Jul 2021
Variational Rejection Particle Filtering Rahul Sharma S. Banerjee Dootika Vats Piyush Rai BDL 64 0 0 29 Mar 2021
Bayesian Neural Ordinary Differential Equations Raj Dandekar Karen Chung Vaibhav Dixit Mohamed Tarek Aslan Garcia-Valadez Krishna Vishal Vemula Chris Rackauckas UQCV OOD BDL 67 53 0 14 Dec 2020
MCMC-Interactive Variational Inference Quan Zhang Huangjie Zheng Mingyuan Zhou 54 1 0 02 Oct 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 219 1,722 0 05 Dec 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 97 144 0 17 Jul 2019
A Contrastive Divergence for Combining Variational Inference and MCMC Francisco J. R. Ruiz Michalis K. Titsias BDL 69 60 0 10 May 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 76 108 0 09 Mar 2019
Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems Yibo Yang P. Perdikaris SyDa BDL AI4CE 66 56 0 15 Jan 2019
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference Louis C. Tiao Edwin V. Bonilla F. Ramos BDL OOD 60 7 0 05 Jun 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 233 698 0 15 Nov 2017
ZhuSuan: A Library for Bayesian Deep Learning Jiaxin Shi Jianfei Chen Jun Zhu Shengyang Sun Yucen Luo Yihong Gu Yuhao Zhou UQCV BDL 82 43 0 18 Sep 2017