Deep Learning Publication Navigator - subtopic: gaussian

Year TitleAuthor
2017   Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods  T Kim, J Park, S Heo, K Sung, J Park
2017   Neural Networks retrieving Boolean patterns in a sea of Gaussian ones  E Agliari, A Barra, C Longo, D Tantari
2017   Deep Learning with Low Precision by Half-wave Gaussian Quantization  Z Cai, X He, J Sun, N Vasconcelos
2017   Gaussian Filter in CRF Based Semantic Segmentation  Y Gu, Q Wu, J Li, K Cheng
2017   Doubly Stochastic Variational Inference for Deep Gaussian Processes  H Salimbeni, M Deisenroth
2017   Unifying the Stochastic Spectral Descent for Restricted Boltzmann Machines with Bernoulli or Gaussian Inputs  K Fan
2017   Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks  J Bradshaw, AGG Matthews, Z Ghahramani
2017   Restricted Boltzmann Machines with Gaussian Visible Units Guided by Pairwise Constraints  J Chu, H Wang, H Meng, P Jin, T Li
2017   Classification of MRI data using Deep Learning and Gaussian Process-based Model Selection  H Bertrand, M Perrot, R Ardon, I Bloch
2017   Annealing Gaussian Into Relu: A New Sam-Pling Strategy For Leaky-Relu Rbm  CLLS Ravanbakhsh, B Póczos
2017   Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes  T Iwata, Z Ghahramani
2017   Biasing Restricted Boltzmann Machines using Gaussian Filters to Learn Invariant Visual Features  A Yogeswaran, P Payeur
2016   Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data  J You, X Li, M Low, D Lobell, S Ermon
2016   Inverse Reinforcement Learning via Deep Gaussian Process  M Jin, C Spanos
2016   Annealing Gaussian into ReLU: a New Sampling Strategy for Leaky-ReLU RBM  CL Li, S Ravanbakhsh, B Poczos
2016   Gaussian Neuron in Deep Belief Network for Sentiment Prediction  Y Jin, D Du, H Zhang
2016   Large Scale Gaussian Process for Overlap-based Object Proposal Scoring  SL Pintea, S Karaoglu, JC van Gemert
2016   Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs  S Chandra, I Kokkinos
2016   The Variational Gaussian Process  D Tran, R Ranganath, DM Blei
2016   Probabilistic Feature Learning Using Gaussian Process Auto-Encoders  S Olofsson
2016   R2C: Improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter  J Yang, QY Jin, B Zhang, HB Shen
2016   Deep, Dense, and Low-Rank Gaussian Conditional Random Fields  S Chandra, I Kokkinos
2016   Sequential Inference for Deep Gaussian Process  Y Wang, M Brubaker, B Chaib
2016   Multi-task and Multi-kernel Gaussian Process Dynamical Systems  D Korkinof, Y Demiris
2016   Gaussian Copula Variational Autoencoders for Mixed Data  S Suh, S Choi
2016   Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising  K Zhang, W Zuo, Y Chen, D Meng, L Zhang
2016   Image super-resolution using non-local Gaussian process regression  H Wang, X Gao, K Zhang, J Li
2016   A Novel Bearing Fault Diagnosis Method based on Gaussian Restricted Boltzmann Machine  X HE, Y LI, C ZHOU
2016   Gaussian Conditional Random Field Network for Semantic Segmentation  R Vemulapalli, O Tuzel, MY Liu, R Chellappa
2016   Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors  C Louizos, M Welling
2016   Deep Gaussian Processes for Regression using Approximate Expectation Propagation  TD Bui, D Hernández
2015   Learning to Assess Terrain from Human Demonstration Using an Introspective Gaussian Process Classifier  LP Berczi, I Posner, TD Barfoot
2015   Assessing the Degree of Nativeness and Parkinson's Condition Using Gaussian Processes and Deep Rectifier Neural Networks  T Grósz, R Busa
2015   Gaussian processes methods for nostationary regression  L Muñoz González
2015   Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?  R Giryes, G Sapiro, AM Bronstein
2015   Nonlinear Gaussian Belief Network based fault diagnosis for industrial processes  H Yu, F Khan, V Garaniya
2015   Interactions Between Gaussian Processes and Bayesian Estimation  YL Wang
2015   Gaussian discrete restricted Boltzmann machine: theory and its applications: a thesis presented in partial fulfilment of the requirements for the degree of Master of …  S Manoharan
2015   Prosody Generation Using Frame-based Gaussian Process Regression  T Koriyama, T Kobayashi
2015   Mean-Field Inference in Gaussian Restricted Boltzmann Machine  C Takahashi, M Yasuda
2015   Variational Auto-encoded Deep Gaussian Processes  Z Dai, A Damianou, J González, N Lawrence
2015   Training Deep Gaussian Processes using Stochastic Expectation Propagation and Probabilistic Backpropagation  TD Bui, JM Hernández
2015   Accurate Object Detection and Semantic Segmentation using Gaussian Mixture Model and CNN  S Jain, S Dehriya, YK Jain
2014   Non-negative Factor Analysis of Gaussian Mixture Model Weight Adaptation for Language and Dialect Recognition  J Glass
2014   Cross Modal Deep Model and Gaussian Process Based Model for MSR-Bing Challenge  J Wang, C Kang, Y He, S Xiang, C Pan
2014   Gaussian Process Models with Parallelization and GPU acceleration  Z Dai, A Damianou, J Hensman, N Lawrence
2014   Parametric Speech Synthesis Using Local and Global Sparse Gaussian  T Koriyama, T Nose, T Kobayashi
2014   On the Link Between Gaussian Homotopy Continuation and Convex Envelopes  H Mobahi, JW Fisher III
2014   Improving Deep Neural Networks Using State Projection Vectors Of Subspace Gaussian Mixture Model As Features  M Karthick, S Umesh
2014   A Theoretical Analysis of Optimization by Gaussian Continuation  H Mobahi, JW Fisher III
2014   Factoring Variations in Natural Images with Deep Gaussian Mixture Models  A van den Oord, B Schrauwen
2014   Feature representation with Deep Gaussian processes  A Damianou