Year  Title  Author 
2017

Learning Local Responses of Facial Landmarks with Conditional Variational AutoEncoder for Face Alignment 
S Liu, Y Huang, J Hu, W Deng

2017

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT 
M Lopez

2017

Supplementary Material for Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks 
L Mescheder, S Nowozin, A Geiger

2017

Implicit Variational Inference with Kernel Density Ratio Fitting 
J Shi, S Sun, J Zhu

2017

A Recurrent Variational Autoencoder for Human Motion Synthesis 
I Habibie, D Holden, J Schwarz, J Yearsley, T Komura

2017

Evaluating deep variational autoencoders trained on pancancer gene expression 
GP Way, CS Greene

2017

Interpreting Neural Network Classifications with Variational Dropout Saliency Maps 
CH Chang, E Creager, A Goldenberg, D Duvenaud

2017

The Deep Ritz method: A deep learningbased numerical algorithm for solving variational problems 
B Yu

2017

A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders 
A Mishra, M Reddy, A Mittal, HA Murthy

2017

Doubly Stochastic Variational Inference for Deep Gaussian Processes 
H Salimbeni, M Deisenroth

2017

Filtering Variational Objectives 
CJ Maddison, D Lawson, G Tucker, N Heess

2017

MultiLevel Variational Autoencoder: Learning Disentangled Representations from Grouped Observations 
D Bouchacourt, R Tomioka, S Nowozin

2017

Transfer learning from synthetic to real images using variational autoencoders for robotic applications 
T Inoue, S Chaudhury, G De Magistris, S Dasgupta

2017

Disentangling Variational Autoencoders for Image Classification 
C Varano

2017

Adversarial Variational Optimization of NonDifferentiable Simulators 
G Louppe, K Cranmer

2017

Learning a Variational Network for Reconstruction of Accelerated MRI Data 
K Hammernik, T Klatzer, E Kobler, MP Recht

2017

Variational Deep Semantic Hashing for Text Documents 
S Chaidaroon, Y Fang

2017

Variational Approaches for AutoEncoding Generative Adversarial Networks 
M Rosca, B Lakshminarayanan, D Warde

2017

Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks 
L Mescheder, S Nowozin, A Geiger

2017

GenerativeDiscriminative Variational Model for Visual Recognition 
CK Yeh, YHH Tsai, YCF Wang

2017

InfoVAE: Information Maximizing Variational Autoencoders 
S Zhao, J Song, S Ermon

2017

Improving Variational AutoEncoders using convex combination linear Inverse Autoregressive Flow 
JM Tomczak, M Welling

2017

Symmetric Variational Autoencoder and Connections to Adversarial Learning 
Y Pu, L Chen, S Dai, W Wang, C Li, L Carin

2017

Recursive Extraction of Modular Structure from Layered Neural Networks Using Variational Bayes Method 
C Watanabe, K Hiramatsu, K Kashino

2017

Learnable Explicit Density for Continuous Latent Space and Variational Inference 
CW Huang, A Touati, L Dinh, M Drozdzal, M Havaei

2017

Hierarchical Implicit Models and LikelihoodFree Variational Inference 
D Tran, R Ranganath, D Blei

2017

Efficient variational Bayesian neural network ensembles for outlier detection 
N Pawlowski, M Jaques, B Glocker

2017

VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning 
A Srivastava, L Valkov, C Russell, M Gutmann

2017

Variational Inference Methods for Tweedie Compound Poisson Models 
Y Yang, S Demyanov, Y Liu, J Wang

2017

GLSRVAE: Geodesic Latent Space Regularization for Variational AutoEncoder Architectures 
G Hadjeres, F Nielsen, F Pachet

2017

Fast amortized inference of neural activity from calcium imaging data with variational autoencoders 
A Speiser, J Yan, E Archer, L Buesing, S Turaga

2017

Variational Inference of Disentangled Latent Concepts from Unlabeled Observations 
A Kumar, P Sattigeri, A Balakrishnan

2017

Learning to Draw Samples with Amortized Stein Variational Gradient Descent 
Y Feng, D Wang, Q Liu

2017

The shape variational autoencoder: A deep generative model of partsegmented 3D objects 
C Nash, CKI Williams

2017

Unsupervised Domain Adaptation for Robust Speech Recognition via Variational AutoencoderBased Data Augmentation 
WN Hsu, Y Zhang, J Glass

2017

Tackling Overpruning in Variational Autoencoders 
S Yeung, A Kannan, Y Dauphin, L Fei

2017

ChannelRecurrent Variational Autoencoders 
W Shang, K Sohn, Z Akata, Y Tian

2017

Learning Model Reparametrizations: Implicit Variational Inference by Fitting MCMC distributions 
MK Titsias

2016

How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks 
CK Sønderby, T Raiko, L Maaløe, SK Sønderby

2016

Variational Graph AutoEncoders 
TN Kipf, M Welling

2016

Discrete Variational Autoencoders 
JT Rolfe

2016

Stochastic Variational Deep Kernel Learning 
AG Wilson, Z Hu, R Salakhutdinov, EP Xing

2016

Summer school on semisupervised learning Variational learning part 2 Autoencoders for unand semisupervised learning 
O Winther

2016

The Variational Gaussian Process 
D Tran, R Ranganath, DM Blei

2016

Generative Adversarial Networks as Variational Training of Energy Based Models 
S Zhai, Y Cheng, R Feris, Z Zhang

2016

Tutorial on Variational Autoencoders 
C Doersch

2016

Deep Feature Consistent Variational Autoencoder 
X Hou, L Shen, K Sun, G Qiu

2016

An Uncertain Future: Forecasting from Static Images using Variational Autoencoders 
J Walker, C Doersch, A Gupta, M Hebert

2016

Gaussian Copula Variational Autoencoders for Mixed Data 
S Suh, S Choi

2016

Multidigit Image Synthesis Using Recurrent Conditional Variational Autoencoder 
H Sun, W Xu, C Deng, Y Tan

2016

Variational methods for Conditional Multimodal Learning: Generating Human Faces from Attributes 
G Pandey, A Dukkipati

2016

Semisupervised Variational Autoencoders for Sequence Classification 
W Xu, H Sun

2016

Echostate conditional variational autoencoder for anomaly detection 
S Suh, DH Chae, HG Kang, S Choi

2016

Variational methods for Conditional Multimodal Deep Learning 
G Pandey, A Dukkipati

2016

Variational Autoencoder for Deep Learning of Images, Labels and Captions 
Y Pu, Z Gan, R Henao, X Yuan, C Li, A Stevens

2016

Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors 
C Louizos, M Welling

2016

Infinite Variational Autoencoder for SemiSupervised Learning 
E Abbasnejad, A Dick, A Hengel

2015

Tight Variational Bounds via Random Projections and IProjections 
LK Hsu, T Achim, S Ermon

2015

Variational Bayesian PHD Filter with Deep Learning Network Updating for Multiple Human Tracking 
P Feng, W Wang, SM Naqvi, J Chambers

2015

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference 
Y Gal, Z Ghahramani

2015

Bilevel approaches for learning of variational imaging models 
L Calatroni, C Chung, JCDL Reyes, CB Schönlieb

2015

Manifold Learning with Variational Autoencoder for Medical Image Analysis 
E Park

2015

A Unifying Variational Inference Framework for Hierarchical GraphCoupled HMM with an Application to Influenza Infection 
K Fan, C Li, K Heller

2015

Fast SecondOrder Stochastic Backpropagation for Variational Inference 
K Fan, Z Wang, J Beck, J Kwok, K Heller

2015

Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning 
S Mohamed, DJ Rezende

2015

Variational Autoencoded Deep Gaussian Processes 
Z Dai, A Damianou, J González, N Lawrence

2015

On Modern Deep Learning and Variational Inference 
Y Gal, Z Ghahramani

2014

An exact mapping between the Variational Renormalization Group and Deep Learning 
P Mehta, DJ Schwab
