Deep Learning Publication Navigator - subtopic: variational


Year TitleAuthor
2017   Learning Local Responses of Facial Landmarks with Conditional Variational Auto-Encoder 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 pan-cancer 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 learning-based 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   Multi-Level 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 Non-Differentiable 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 Auto-Encoding 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   Generative-Discriminative 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 Auto-Encoders 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 Likelihood-Free 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   GLSR-VAE: 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 part-segmented 3D objects  C Nash, CKI Williams
2017   Unsupervised Domain Adaptation for Robust Speech Recognition via Variational Autoencoder-Based Data Augmentation  WN Hsu, Y Zhang, J Glass
2017   Tackling Over-pruning in Variational Autoencoders  S Yeung, A Kannan, Y Dauphin, L Fei
2017   Channel-Recurrent 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 Auto-Encoders  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 Auto-encoders for un-and 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   Multi-digit 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   Semi-supervised Variational Autoencoders for Sequence Classification  W Xu, H Sun
2016   Echo-state 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 Semi-Supervised Learning  E Abbasnejad, A Dick, A Hengel
2015   Tight Variational Bounds via Random Projections and I-Projections  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 Auto-encoder for Medical Image Analysis  E Park
2015   A Unifying Variational Inference Framework for Hierarchical Graph-Coupled HMM with an Application to Influenza Infection  K Fan, C Li, K Heller
2015   Fast Second-Order 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 Auto-encoded 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