On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder

31 May 2019

Papers citing "On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder"

10 / 10 papers shown

Title
Weakly Supervised Bayesian Shape Modeling from Unsegmented Medical Images Jadie Adams Krithika S. Iyer Shireen Elhabian 24 2 0 15 May 2024
Learning Nonparametric High-Dimensional Generative Models: The Empirical-Beta-Copula Autoencoder Maximilian Coblenz Oliver Grothe Fabian Kächele SyDa DRL 28 1 0 18 Sep 2023
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting Shayan Shirahmad Gale Bagi Zahra Gharaee Oliver Schulte Mark Crowley OODD OOD 23 12 0 17 Feb 2023
Improving Variational Autoencoders with Density Gap-based Regularization Jianfei Zhang Jun Bai Chenghua Lin Yanmeng Wang Wenge Rong DRL 31 4 0 01 Nov 2022
RENs: Relevance Encoding Networks Krithika S. Iyer Riddhish Bhalodia Shireen Elhabian DRL 13 1 0 25 May 2022
A Contextual Latent Space Model: Subsequence Modulation in Melodic Sequence Taketo Akama BDL 22 3 0 23 Nov 2021
A Contrastive Learning Approach for Training Variational Autoencoder Priors J. Aneja A. Schwing Jan Kautz Arash Vahdat DRL 6 81 0 06 Oct 2020
RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback Ilya Shenbin Anton M. Alekseev E. Tutubalina Valentin Malykh Sergey I. Nikolenko BDL DRL 16 196 0 24 Dec 2019
dpVAEs: Fixing Sample Generation for Regularized VAEs Riddhish Bhalodia Iain Lee Shireen Elhabian DRL 6 10 0 24 Nov 2019
Graph Generation with Variational Recurrent Neural Network Shih-Yang Su Shunwei Lei Greg Mori GAN GNN 25 17 0 02 Oct 2019