Deep Learning Publication Navigator - subtopic: autoencoders


Year TitleAuthor
2017   Multi channel brain EEG signals based emotional arousal classification with unsupervised feature learning using autoencoders  D Ayata, Y Yaslan, M Kamasak
2017   Neuroevolution of Autoencoders by Genetic Algorithm  H Okada
2017   Training autoencoders for state estimation in smart grids  RMM Oliveira
2017   Supplementary Material for Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks  L Mescheder, S Nowozin, A Geiger
2017   On the Evaluation of Energy-Efficient Deep Learning Using Stacked Autoencoders on Mobile GPUs  G Falcao, LA Alexandre, J Marques, X Frazao, J Maria
2017   Constructing a Deep Regression Model Utilizing Cascaded Sparse Autoencoders and Stochastic Gradient Descent  A Moussavi
2017   A deep learning framework for financial time series using stacked autoencoders and long-short term memory.  W Bao, J Yue, Y Rao
2017   Deep belief networks and stacked autoencoders for the P300 Guilty Knowledge Test  JP Kulasingham, V Vibujithan, AC De Silva
2017   A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders  A Mishra, M Reddy, A Mittal, HA Murthy
2017   Discriminative Autoencoders for Acoustic Modeling  MH Yang, HS Lee, YD Lu, KY Chen, Y Tsao, B Chen
2017   Stacked autoencoders for the P300 component detection  L Vareka, P Mautner
2017   Stacked Denoising Autoencoders Applied to Star/Galaxy Classification  Q Hao
2017   Learning Musical Relations using Gated Autoencoders  S Lattner, M Grachten, G Widmer
2017   Infant Asphyxia Detection Using Autoencoders Trained On Locally Linear Embedded-Reduced Mel Frequency Cepstrum …  IM Yassin, A Zabidi, N Ismail, FHK Zaman, MF Shafie
2017   Transfer learning from synthetic to real images using variational autoencoders for robotic applications  T Inoue, S Chaudhury, G De Magistris, S Dasgupta
2017   Hyperspectral anomaly detection based on stacked denoising autoencoders  C Zhao, X Li, H Zhu
2017   On denoising autoencoders trained to minimise binary cross-entropy  A Creswell, K Arulkumaran, AA Bharath
2017   Dimensionality Reduction for Image Features using Deep Learning and Autoencoders  S Petscharnig, M Lux, S Chatzichristofis
2017   Disentangling Variational Autoencoders for Image Classification  C Varano
2017   PixelGAN Autoencoders  A Makhzani, B Frey
2017   Adversarially Regularized Autoencoders for Generating Discrete Structures  Y Kim, K Zhang, AM Rush, Y LeCun
2017   Learning and Evaluating Musical Features with Deep Autoencoders  M Bretan, S Oore, D Eck, L Heck
2017   Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks  L Mescheder, S Nowozin, A Geiger
2017   InfoVAE: Information Maximizing Variational Autoencoders  S Zhao, J Song, S Ermon
2017   Hallucinating Very Low-Resolution Unaligned and Noisy Face Images by Transformative Discriminative Autoencoders  X Yu, F Porikli
2017   Recognition of Human Activities in Smart Homes Using Stacked Autoencoders  NEH Mbarki, R Ejbali, M Zaied
2017   Deep Kernelized Autoencoders  M Kampffmeyer, S Løkse, FM Bianchi, R Jenssen
2017   A deep learning framework for financial time series using stacked autoencoders and long-short term memory  W Bao, J Yue, Y Rao
2017   Automatic Modulation Classification Using Deep Learning based on Sparse Autoencoders with Non-negativity Constraints  A Ali, F Yangyu
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   Deep Learning Quantification: Extracting Quantitative Information from Images using Convolutional Autoencoders  A Azzini
2017   Discovery Through Constraints: Imposing Constraints on Autoencoders for Data Representation and Dictionary Learning  BO Ayinde, JM Zurada
2017   Nonredundant sparse feature extraction using autoencoders with receptive fields clustering  BO Ayinde, JM Zurada
2017   Knock-Knock: Acoustic Object Recognition by using Stacked Denoising Autoencoders  S Luo, L Zhu, K Althoefer, H Liu
2017   GRASS: Generative Recursive Autoencoders for Shape Structures  J Li, K Xu, S Chaudhuri, E Yumer, H Zhang, L Guibas
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   Unsupervised feature-learning for galaxy SEDs with denoising autoencoders  J Frontera
2016   A Map-Reduce Method for Training Autoencoders on Xeon Phi  Q Yao, X Liao, H Jin
2016   Three-dimensional image-based human pose recovery with hypergraph regularized autoencoders  C Hong, J Yu, Y Jane, Z Yu, X Chen
2016   How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks  CK Sønderby, T Raiko, L Maaløe, SK Sønderby
2016   Deep Network based on Stacked Orthogonal Convex Incremental ELM Autoencoders  C Wang, J Wang, S Gu
2016   Collaborative Filtering with Stacked Denoising AutoEncoders and Sparse Inputs  F Strub, J Mary
2016   Discrete Variational Autoencoders  JT Rolfe
2016   Online Bengali Handwritten Numerals Recognition Using Deep Autoencoders  A Pal, BK Khonglah, S Mandal, H Choudhury
2016   Fishing activity detection from AIS data using autoencoders  X Jiang, DL Silver, B Hu, EN de Souza, S Matwin
2016   Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hi-speed Flame Video  A Akintayo, KG Lore, S Sarkar, S Sarkar
2016   Learning Robust Uniform Features for Cross-media Social Data by Using Cross Autoencoders  Q Guo, J Jia, G Shen, L Zhang, L Cai, Z Yi
2016   Improving Deep Learning Accuracy with Noisy Autoencoders Embedded Perturbative Layers  L Xia, X Zhang, B Li
2016   Composite denoising autoencoders  KJ Geras, C Sutton
2016   Semi-supervised Learning using Denoising Autoencoders for Brain Lesion Detection and Segmentation  V Alex, K Vaidhya, S Thirunavukkarasu, C Kesavdas
2016   Semi-supervised classification of hyperspectral imagery based on stacked autoencoders  Q Fu, X Yu, X Wei, Z Xue
2016   Towards 3D object recognition with contractive autoencoders  B Liu, L Kong, J Zhao, J Wu, Z Tan
2016   Recognition of Human Activities Using Continuous Autoencoders with Wearable Sensors  L Wang
2016   FPGA Implementation of Autoencoders Having Shared Synapse Architecture  A Suzuki, T Morie, H Tamukoh
2016   Features Learning and Transformation Based on Deep Autoencoders  E Janvier, T Couronne, N Grozavu
2016   Tutorial on Variational Autoencoders  C Doersch
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   Churn analysis using deep convolutional neural networks and autoencoders  A Wangperawong, C Brun, O Laudy, R Pavasuthipaisit
2016   Protein Residue-Residue Contact Prediction Using Stacked Denoising Autoencoders  IV Luttrell, J Bailey
2016   Semi-supervised Variational Autoencoders for Sequence Classification  W Xu, H Sun
2016   Faster learning of deep stacked autoencoders on multi-core systems using synchronized layer-wise pre-training  A Santara, D Maji, DP Tejas, P Mitra, A Gupta
2016   DeepPainter: Painter Classification Using Deep Convolutional Autoencoders  OE David, NS Netanyahu
2016   A Time Series Forecasting Model Based on Deep Learning Integrated Algorithm with Stacked Autoencoders and SVR for FX Prediction  H Shen, X Liang
2016   Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology  A Janowczyk, A Basavanhally, A Madabhushi
2016   A Domain Adaptation Regularization for Denoising Autoencoders  S Clinchant, G Csurka, B Chidlovskii
2016   Regularized autoencoders  K Gupta, A Majumdar
2016   Importance Weighted Autoencoders with Random Neural Network Parameters  D Hernández
2016   Multi-modal Image Re-ranking with Autoencoders and Click Semantics  C Tang, Q Zhu, C Hong, J Yu
2016   Learning Multiple Views with Orthogonal Denoising Autoencoders  TQ Ye, T Wang, K McGuinness, Y Guo, C Gurrin
2016   Fault detection for ironmaking process based on stacked denoising autoencoders  T Zhang, W Wang, H Ye, DX Huang, H Zhang, M Li
2016   Autoencoders with Drop Strategy  C Hu, XJ Wu
2015   Multimodal fusion for sensor data using stacked autoencoders  P Zhang, X Ma, W Zhang, S Lin, H Chen, AL Yirun
2015   High-Resolution SAR Image Classification via Deep Convolutional Autoencoders  J Geng, J Fan, H Wang, X Ma, B Li, F Chen
2015   Correspondence Autoencoders for Cross-Modal Retrieval  F Feng, X Wang, R Li, I Ahmad
2015   Feature Learning Using Stacked Autoencoders to Predict the Activity of Antimicrobial Peptides  F Camacho, R Torres, R Ramos
2015   Evaluating Stacked Marginalised Denoising Autoencoders Within Domain Adaptation Methods  B Chidlovskii, G Csurka, S Clinchant
2015   Stacked Autoencoders Using Low-Power Accelerated Architectures for Object Recognition in Autonomous Systems  J Maria, J Amaro, G Falcao, LA Alexandre
2015   Reverberant speech recognition combining deep neural networks and deep autoencoders augmented with a phone-class feature  M Mimura, S Sakai, T Kawahara
2015   Denoising Convolutional Autoencoders for Noisy Speech Recognition  M Kayser, V Zhong
2015   Training Stacked Denoising Autoencoders for Representation Learning  J Liang, K Kelly
2015   Denoising Autoencoders for fast Combinatorial Black Box Optimization  M Probst
2015   Convergence of gradient based pre-training in Denoising autoencoders  VK Ithapu, S Ravi, V Singh
2015   Pedestrian Detection in RGB-D Data Using Deep Autoencoders  PA Kazantsev, PV Skribtsov
2015   Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders  C Finn, XY Tan, Y Duan, T Darrell, S Levine, P Abbeel
2015   Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints  E Hosseini
2015   Cross-lingual sentiment classification with stacked autoencoders  G Zhou, Z Zhu, T He, XT Hu
2015   Marginalizing Stacked Linear Denoising Autoencoders  M Chen, KQ Weinberger, ZE Xu, F Sha
2015   Learning Deep State Representations With Convolutional Autoencoders  G Barth
2015   Importance Weighted Autoencoders  Y Burda, R Grosse, R Salakhutdinov
2015   Online Semi-Supervised Learning with Deep Hybrid Boltzmann Machines and Denoising Autoencoders  II Ororbia, G Alexander, CL Giles, D Reitter
2015   A study on the similarities of Deep Belief Networks and Stacked Autoencoders  A Holst, A de Giorgio, A Lansner
2015   Multimodal Video Classification with Stacked Contractive Autoencoders  Y Liu, X Feng, Z Zhou
2015   Multimodal Deep Autoencoders for Control of a Mobile Robot  J Sergeant, N Sünderhauf, M Milford, B Upcroft
2015   Winner-Take-All Autoencoders  A Makhzani, BJ Frey
2015   Marginalised Stacked Denoising Autoencoders for Robust Representation of Real-Time Multi-View Action Recognition  F Gu, F Flórez
2015   Adversarial Autoencoders  A Makhzani, J Shlens, N Jaitly, I Goodfellow
2014   Static hand gesture recognition using stacked Denoising Sparse Autoencoders  V Kumar, GC Nandi, R Kala
2014   Improving generation performance of speech emotion recognition by denoising autoencoders  L Chao, J Tao, M Yang, Y Li
2014   Chord Recognition with Stacked Denoising Autoencoders  N Steenbergen
2014   Introduction to Autoencoders  D Meyer
2014   Pre-training of Recurrent Neural Networks via Linear Autoencoders  L Pasa, A Sperduti
2014   Deep Directed Generative Autoencoders  S Ozair, Y Bengio
2014   Recognition of Handwritten Characters in Chinese Legal Amounts by Stacked Autoencoders  M Wang, Y Chen, X Wang
2014   Feature extraction with stacked autoencoders for epileptic seizure detection  A Supratak, L Li, Y Guo