Conditional Density Estimation with Bayesian Normalising Flows

14 February 2018

Papers citing "Conditional Density Estimation with Bayesian Normalising Flows"

22 / 22 papers shown

Title
Accelerate TarFlow Sampling with GS-Jacobi Iteration Ben Liu Zhen Qin 73 0 0 19 May 2025
Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks Benjamin Cox Santiago Segarra Victor Elvira 128 0 0 23 Nov 2024
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner Valentyn Melnychuk Stefan Feuerriegel Mihaela van der Schaar CML 235 5 0 05 Nov 2024
Benchmarking Counterfactual Image Generation Thomas Melistas Nikos Spyrou Nefeli Gkouti Pedro Sanchez Athanasios Vlontzos Yannis Panagakis G. Papanastasiou Sotirios A. Tsaftaris EGVM CML 79 9 0 29 Mar 2024
Probabilistic Forecasting of Irregular Time Series via Conditional Flows Vijaya Krishna Yalavarthi Randolf Scholz Stefan Born Lars Schmidt-Thieme AI4TS 115 0 0 09 Feb 2024
Deep Structural Causal Models for Tractable Counterfactual Inference Nick Pawlowski Daniel Coelho De Castro Ben Glocker CML MedIm 106 238 0 11 Jun 2020
Overpruning in Variational Bayesian Neural Networks Brian L. Trippe Richard Turner BDL 57 53 0 18 Jan 2018
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 210 1,354 0 19 May 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 129 197 0 08 Mar 2017
Conditional Image Generation with PixelCNN Decoders Aaron van den Oord Nal Kalchbrenner Oriol Vinyals L. Espeholt Alex Graves Koray Kavukcuoglu VLM 209 2,513 0 16 Jun 2016
Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks Stefan Depeweg José Miguel Hernández-Lobato Finale Doshi-Velez Steffen Udluft BDL 55 160 0 23 May 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 165 158 0 20 May 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 60 257 0 15 Mar 2016
Deep Gaussian Processes for Regression using Approximate Expectation Propagation T. Bui Daniel Hernández-Lobato Yingzhen Li José Miguel Hernández-Lobato Richard Turner BDL 131 237 0 12 Feb 2016
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 226 1,514 0 08 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 313 4,182 0 21 May 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 187 1,887 0 20 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 130 946 0 18 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Conditional Generative Adversarial Nets M. Berk Mirza Simon Osindero GAN SyDa AI4CE 258 10,409 0 06 Nov 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 126 2,261 0 30 Oct 2014
A Deep and Tractable Density Estimator Benigno Uria Iain Murray Hugo Larochelle BDL 101 194 0 07 Oct 2013