Improving Variational Auto-Encoders using Householder Flow

29 November 2016

Papers citing "Improving Variational Auto-Encoders using Householder Flow"

36 / 36 papers shown

Title
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 64 0 0 03 Jan 2025
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 54 5 0 08 Apr 2024
Training Energy-Based Normalizing Flow with Score-Matching Objectives Chen-Hao Chao Wei-Fang Sun Yen-Chang Hsu Z. Kira Chun-Yi Lee 25 2 0 24 May 2023
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks Forough Fazeli Asl M. Zhang Lizhen Lin 24 1 0 05 Mar 2023
Variational Laplace Autoencoders Yookoon Park C. Kim Gunhee Kim BDL DRL 26 21 0 30 Nov 2022
$β$ -Multivariational Autoencoder for Entangled Representation Learning in Video Frames F. Nouri R. Bergevin 16 0 0 22 Nov 2022
An Overview on Controllable Text Generation via Variational Auto-Encoders Haoqin Tu Yitong Li BDL 24 2 0 15 Nov 2022
Sparse Representation Learning with Modified q-VAE towards Minimal Realization of World Model Taisuke Kobayashi Ryoma Watanuki DRL 26 6 0 08 Aug 2022
Mix and Match: An Empirical Study on Training Corpus Composition for Polyglot Text-To-Speech (TTS) Ziyao Zhang Alessio Falai Ariadna Sánchez Orazio Angelini K. Yanagisawa 21 4 0 04 Jul 2022
Latent Variable Modelling Using Variational Autoencoders: A survey Vasanth Kalingeri CML DRL 23 2 0 20 Jun 2022
Flowification: Everything is a Normalizing Flow Bálint Máté Samuel Klein T. Golling Franccois Fleuret 23 3 0 30 May 2022
Variational Inference with Locally Enhanced Bounds for Hierarchical Models Tomas Geffner Justin Domke 29 5 0 08 Mar 2022
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation Abhishek Sinha Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 30 118 0 12 Jun 2021
Review of end-to-end speech synthesis technology based on deep learning Zhaoxi Mu Xinyu Yang Yizhuo Dong AuLLM ALM 26 24 0 20 Apr 2021
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 16 22 0 26 Jun 2020
Categorical Normalizing Flows via Continuous Transformations Phillip Lippe E. Gavves BDL 21 43 0 17 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Jackson Wang Roger C. Grosse J. Jacobsen 23 92 0 16 Jun 2020
Ordering Dimensions with Nested Dropout Normalizing Flows Artur Bekasov Iain Murray DRL 28 5 0 15 Jun 2020
Learning normalizing flows from Entropy-Kantorovich potentials Chris Finlay Augusto Gerolin Adam M. Oberman Aram-Alexandre Pooladian 33 23 0 10 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 25 28 0 02 Jun 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Variational Item Response Theory: Fast, Accurate, and Expressive Mike Wu R. Davis B. Domingue Chris Piech Noah D. Goodman OffRL 24 52 0 01 Feb 2020
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs Shuyu Lin Stephen J. Roberts Niki Trigoni R. Clark DRL 18 15 0 09 Sep 2019
Conditional Flow Variational Autoencoders for Structured Sequence Prediction Apratim Bhattacharyya M. Hanselmann Mario Fritz Bernt Schiele C. Straehle BDL DRL AI4TS 24 83 0 24 Aug 2019
Learning Symmetries of Classical Integrable Systems Roberto Bondesan A. Lamacraft 22 39 0 11 Jun 2019
Variational Autoencoder with Implicit Optimal Priors Hiroshi Takahashi Tomoharu Iwata Yuki Yamanaka Masanori Yamada Satoshi Yagi DRL 26 61 0 14 Sep 2018
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 21 482 0 14 Aug 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 68 4,929 0 19 Jun 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 19 432 0 03 Apr 2018
Sylvester Normalizing Flows for Variational Inference Rianne van den Berg Leonard Hasenclever Jakub M. Tomczak Max Welling BDL DRL 13 249 0 15 Mar 2018
Inference Suboptimality in Variational Autoencoders Chris Cremer Xuechen Li David Duvenaud DRL BDL 27 280 0 10 Jan 2018
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 34 57 0 04 Sep 2017
Bayesian Semisupervised Learning with Deep Generative Models Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV GAN 32 27 0 29 Jun 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks L. Mescheder Sebastian Nowozin Andreas Geiger GAN BDL 34 525 0 17 Jan 2017
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 239 2,550 0 25 Jan 2016