← Models
Deep Learning › Models ›

Generative Models

6381 directly classified papers

Papers per year

Papers

Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks PGM 2018
One-Shot Unsupervised Cross Domain Translation NIPS 2018
Learning Latent Subspaces in Variational Autoencoders NIPS 2018
Faithful Inversion of Generative Models for Effective Amortized Inference NIPS 2018
BourGAN: Generative Networks with Metric Embeddings NIPS 2018
Constructing Unrestricted Adversarial Examples with Generative Models NIPS 2018
Flexible and accurate inference and learning for deep generative models NIPS 2018
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance NIPS 2018
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors NIPS 2018
GumBolt: Extending Gumbel trick to Boltzmann priors NIPS 2018
Memory Replay GANs: Learning to Generate New Categories without Forgetting NIPS 2018
Towards Text Generation with Adversarially Learned Neural Outlines NIPS 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks NIPS 2018
Learning Disentangled Joint Continuous and Discrete Representations NIPS 2018
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo NIPS 2018
Geometry Based Data Generation NIPS 2018
Glow: Generative Flow with Invertible 1x1 Convolutions NIPS 2018
Minimax Estimation of Neural Net Distance NIPS 2018
Are GANs Created Equal? A Large-Scale Study NIPS 2018
Assessing Generative Models via Precision and Recall NIPS 2018
Spherical Latent Spaces for Stable Variational Autoencoders EMNLP 2018
Hierarchical Quantized Representations for Script Generation EMNLP 2018
Pose-Guided Photorealistic Face Rotation CVPR 2018
Visual Feature Attribution Using Wasserstein GANs CVPR 2018
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks CVPR 2018