← Learning Types
Deep Learning › Learning Types ›

Generative Models

1275 directly classified papers

Papers per year

Papers

Human Action Transfer Based on 3D Model Reconstruction AAAI 2019
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation NIPS 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient NIPS 2019
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis NIPS 2019
A Domain Agnostic Measure for Monitoring and Evaluating GANs NIPS 2019
Defending Neural Backdoors via Generative Distribution Modeling NIPS 2019
Characterizing Bias in Classifiers using Generative Models NIPS 2019
Learning from Bad Data via Generation NIPS 2019
Generative Well-intentioned Networks NIPS 2019
Training Language GANs from Scratch NIPS 2019
Emergence of Object Segmentation in Perturbed Generative Models NIPS 2019
Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test NIPS 2019
Invertible Convolutional Flow NIPS 2019
Time-series Generative Adversarial Networks NIPS 2019
Re-examination of the Role of Latent Variables in Sequence Modeling NIPS 2019
Learning Disentangled Representation for Robust Person Re-identification NIPS 2019
Conditional Independence Testing using Generative Adversarial Networks NIPS 2019
Graph-based Discriminators: Sample Complexity and Expressiveness NIPS 2019
Face Reconstruction from Voice using Generative Adversarial Networks NIPS 2019
Deep Generative Video Compression NIPS 2019
The continuous Bernoulli: fixing a pervasive error in variational autoencoders NIPS 2019
Classification Accuracy Score for Conditional Generative Models NIPS 2019
Exploring Human-Like Reading Strategy for Abstractive Text Summarization AAAI 2019
Improving Image Captioning with Conditional Generative Adversarial Nets AAAI 2019
Perceptual Pyramid Adversarial Networks for Text-to-Image Synthesis AAAI 2019