generative modeling

DisARM: An Antithetic Gradient Estimator for Binary Latent Variables NeurIPS 2020 General Purpose MRF Learning with Neural Network Potentials IJCAI 2020 Gradient Boosted Normalizing Flows NeurIPS 2020 Knowledge-Based Regularization in Generative Modeling IJCAI 2020 Learning VAE-LDA Models with Rounded Reparameterization Trick EMNLP 2020 Leveraging 2D Data to Learn Textured 3D Mesh Generation CVPR 2020 Semi-Supervised Learning with Normalizing Flows ICML 2020 The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction CVPR 2020 Weakly-Supervised Action Localization by Generative Attention Modeling CVPR 2020 A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models NeurIPS 2019 BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling NeurIPS 2019 Defending Neural Backdoors via Generative Distribution Modeling NeurIPS 2019 Don't let your Discriminator be fooled ICLR 2019 Generalized Sliced Wasserstein Distances NeurIPS 2019 Improved Conditional VRNNs for Video Prediction ICCV 2019 Learning Flexible Latent Representations via Encapsulated Variational Encoders AAAI 2019 Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets AAAI 2019 Preventing Posterior Collapse with delta-VAEs ICLR 2019 Residual Flows for Invertible Generative Modeling NeurIPS 2019 Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions ICML 2019 Unsupervised Primitive Discovery for Improved 3D Generative Modeling CVPR 2019 Autoregressive Quantile Networks for Generative Modeling ICML 2018 Generalizing Hamiltonian Monte Carlo with Neural Networks ICLR 2018 Geometrically Coupled Monte Carlo Sampling NeurIPS 2018 Learning Independent Causal Mechanisms ICML 2018