generative modeling

Sparse Probabilistic Circuits via Pruning and Growing NeurIPS 2022 Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain Interspeech 2022 Stability Regularization for Discrete Representation Learning ICLR 2022 Transformer-based out-of-distribution detection for clinically safe segmentation MIDL 2022 Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion ICLR 2022 VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids NeurIPS 2022 WeaNF”:" Weak Supervision with Normalizing Flows ACL 2022 Whitening Convergence Rate of Coupling-based Normalizing Flows NeurIPS 2022 Compositional Transformers for Scene Generation NeurIPS 2021 Counterfactual Generative Networks ICLR 2021 Diffusion Normalizing Flow NeurIPS 2021 Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections NeurIPS 2021 Imitation by Predicting Observations ICML 2021 Injecting Entity Types into Entity-Guided Text Generation EMNLP 2021 Moser Flow: Divergence-based Generative Modeling on Manifolds NeurIPS 2021 On Energy-Based Models with Overparametrized Shallow Neural Networks ICML 2021 Optimal Transport for Deep Generative Models: State of the Art and Research Challenges IJCAI 2021 OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport AAAI 2021 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics ICML 2021 Point-Set Distances for Learning Representations of 3D Point Clouds ICCV 2021 Representational aspects of depth and conditioning in normalizing flows ICML 2021 Shapley explainability on the data manifold ICLR 2021 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling ICLR 2021 ACFlow: Flow Models for Arbitrary Conditional Likelihoods ICML 2020 Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance NeurIPS 2020