Learning Hierarchical Priors in VAEs

Learning Hierarchical Priors in VAEs

13 May 2019

Patrick van der Smagt

Papers citing "Learning Hierarchical Priors in VAEs"

19 / 19 papers shown

Title
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 96 1 0 25 Nov 2024
M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling Xudong Sun Nutan Chen Alexej Gossmann Yu Xing Carla Feistner ... Felix Drost Daniele Scarcella Lisa Beer Carsten Marr Carsten Marr 59 1 0 20 Mar 2024
Variational Mixture of HyperGenerators for Learning Distributions Over Functions Batuhan Koyuncu Pablo Sánchez-Martín I. Peis Pablo Martínez Olmos Isabel Valera BDL GAN DRL 27 5 0 13 Feb 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space Model Zhidi Lin Feng Yin Juan Maroñas 34 7 0 21 Jan 2023
eVAE: Evolutionary Variational Autoencoder Zhangkai Wu LongBing Cao Lei Qi BDL DRL 40 10 0 01 Jan 2023
NVDiff: Graph Generation through the Diffusion of Node Vectors Xiaohui Chen Yukun Li Aonan Zhang Liping Liu DiffM 28 21 0 19 Nov 2022
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 42 21 0 15 Sep 2022
Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation Jinyi Hu Xiaoyuan Yi Wenhao Li Maosong Sun Xing Xie 46 21 0 13 Jul 2022
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case Clément Chadebec Louis J. Vincent S. Allassonnière DRL 39 29 0 16 Jun 2022
Efficient-VDVAE: Less is more Louay Hazami Rayhane Mama Ragavan Thurairatnam BDL 29 28 0 25 Mar 2022
VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming Eleonora Misino G. Marra Emanuele Sansone 29 21 0 07 Feb 2022
Multi-Task Neural Processes Jiayi Shen Xiantong Zhen M. Worring Ling Shao BDL 24 8 0 10 Nov 2021
On Incorporating Inductive Biases into VAEs Ning Miao Emile Mathieu N. Siddharth Yee Whye Teh Tom Rainforth CML DRL 32 10 0 25 Jun 2021
Symmetric Wasserstein Autoencoders S. Sun Hong Guo DiffM GAN 26 0 0 24 Jun 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 48 63 0 30 Apr 2021
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models Justin Bayer Maximilian Soelch Atanas Mirchev Baris Kayalibay Patrick van der Smagt 29 15 0 18 Jan 2021
AVAE: Adversarial Variational Auto Encoder Antoine Plumerault Hervé Le Borgne C´eline Hudelot GAN DRL 29 16 0 21 Dec 2020
Variational Autoencoders with Riemannian Brownian Motion Priors Dimitris Kalatzis David Eklund Georgios Arvanitidis Søren Hauberg BDL DRL 60 48 0 12 Feb 2020
Learning Flat Latent Manifolds with VAEs Nutan Chen Alexej Klushyn Francesco Ferroni Justin Bayer Patrick van der Smagt DRL 37 39 0 12 Feb 2020