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Generative Models

6,381 papers

Papers per year

Papers

Improved Techniques for Training Single-Image GANs WACV 2021
Towards Fair Cross-Domain Adaptation via Generative Learning WACV 2021
Shape From Semantic Segmentation via the Geometric Renyi Divergence WACV 2021
Fast and Flexible Temporal Point Processes with Triangular Maps NIPS 2020
Reciprocal Adversarial Learning via Characteristic Functions NIPS 2020
Flows for simultaneous manifold learning and density estimation NIPS 2020
Learning Manifold Implicitly via Explicit Heat-Kernel Learning NIPS 2020
Neural Networks with Recurrent Generative Feedback NIPS 2020
Improving Inference for Neural Image Compression NIPS 2020
Robust compressed sensing using generative models NIPS 2020
Convolutional Generation of Textured 3D Meshes NIPS 2020
Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring NIPS 2020
Deep Archimedean Copulas NIPS 2020
Sinkhorn Natural Gradient for Generative Models NIPS 2020
A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model NIPS 2020
Network-to-Network Translation with Conditional Invertible Neural Networks NIPS 2020
Fourier Spectrum Discrepancies in Deep Network Generated Images NIPS 2020
A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions NIPS 2020
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators NIPS 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks NIPS 2020
Teaching a GAN What Not to Learn NIPS 2020
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models NIPS 2020
Low Distortion Block-Resampling with Spatially Stochastic Networks NIPS 2020
Telescoping Density-Ratio Estimation NIPS 2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations NIPS 2020