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   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   Deep belief networks and stacked autoencoders for the P300 Guilty Knowledge Test  JP Kulasingham, V Vibujithan, AC De Silva
2017   Stacked autoencoders for the P300 component detection  L Vareka, P Mautner
2017   Stacked Denoising Autoencoders Applied to Star/Galaxy Classification  Q Hao
2017   PixelGAN Autoencoders  A Makhzani, B Frey
2017   Learning and Evaluating Musical Features with Deep Autoencoders  M Bretan, S Oore, D Eck, L Heck
2017   Adversarially Regularized Autoencoders for Generating Discrete Structures  Y Kim, K Zhang, AM Rush, Y LeCun
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   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   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   How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks  CK Sønderby, T Raiko, L Maaløe, SK Sønderby
2016   Three-dimensional image-based human pose recovery with hypergraph regularized autoencoders  C Hong, J Yu, Y Jane, Z Yu, X Chen
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