Diffusion Models

Variational Diffusion Models NeurIPS 2021 WaveGrad: Estimating Gradients for Waveform Generation ICLR 2021 ACFlow: Flow Models for Arbitrary Conditional Likelihoods ICML 2020 Analyzing and Improving the Image Quality of StyleGAN CVPR 2020 Conditional Generative Neural Decoding with Structured CNN Feature Prediction AAAI 2020 Denoising Diffusion Probabilistic Models NeurIPS 2020 Diffusion Variational Autoencoders IJCAI 2020 Exchangeable Generative Models with Flow Scans AAAI 2020 Further Analysis of Outlier Detection with Deep Generative Models NeurIPS 2020 GAN Memory with No Forgetting NeurIPS 2020 GTCOM Neural Machine Translation Systems for WMT20 EMNLP 2020 Improved Techniques for Training Score-Based Generative Models NeurIPS 2020 Neural Manifold Ordinary Differential Equations NeurIPS 2020 Normalizing Flows With Multi-Scale Autoregressive Priors CVPR 2020 Structured Output Learning with Conditional Generative Flows AAAI 2020 Why Normalizing Flows Fail to Detect Out-of-Distribution Data NeurIPS 2020 Woodbury Transformations for Deep Generative Flows NeurIPS 2020 Co-Generation with GANs using AIS based HMC NeurIPS 2019 Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN ICML 2019 Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing AAAI 2019 Joint Manifold Diffusion for Combining Predictions on Decoupled Observations CVPR 2019 Theoretical guarantees for sampling and inference in generative models with latent diffusions COLT 2019 DifNet: Semantic Segmentation by Diffusion Networks NeurIPS 2018 VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection CVPR 2018 Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling NeurIPS 2016