conftrace_

generative model

2892 papers

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Also known as

GM

Co-occurring keywords

diffusion model (3751) image generation (2073) variational autoencoder (1288) variational inference (2069) neural network (6616) latent space (854) generative adversarial network (1944) representation learning (6206) unsupervised learning (3264) normalizing flow (354)

Papers

Wasserstein Training of Restricted Boltzmann Machines NIPS 2016
Conditional Generative Moment-Matching Networks NIPS 2016
Data Programming: Creating Large Training Sets, Quickly NIPS 2016
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models JMLR 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization NIPS 2016
On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification PGM 2016
Auxiliary Deep Generative Models ICML 2016
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models NIPS 2016
Bidirectional Helmholtz Machines ICML 2016
Factored Temporal Sigmoid Belief Networks for Sequence Learning ICML 2016
Learning to Generate with Memory ICML 2016
Learning Temporal Regularity in Video Sequences CVPR 2016
Modeling and Transforming Speech Using Variational Autoencoders INTERSPEECH 2016
Generative Acoustic-Phonemic-Speaker Model Based on Three-Way Restricted Boltzmann Machine INTERSPEECH 2016
Neural Autoregressive Distribution Estimation JMLR 2016
Universal Approximation Results for the Temporal Restricted Boltzmann Machine and the Recurrent Temporal Restricted Boltzmann Machine JMLR 2016
Iterative Refinement of the Approximate Posterior for Directed Belief Networks NIPS 2016
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization AISTATS 2016
Dynamic Generative model for Diachronic Sense Emergence Detection COLING 2016
Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016
Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis CVPR 2016
PHOG: Probabilistic Model for Code ICML 2016
Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Learn Neural Networks JMLR 2016
Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data NIPS 2016
Accelerated Generative Models for 3D Point Cloud Data CVPR 2016