Variational Inference

Sparse Communication via Mixed Distributions ICLR 2022 Sparse Fourier Backpropagation in Cryo-EM Reconstruction NeurIPS 2022 Split Hierarchical Variational Compression CVPR 2022 SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion NeurIPS 2022 SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization ICML 2022 Stochastic Multiple Target Sampling Gradient Descent NeurIPS 2022 Structured Recognition for Generative Models with Explaining Away NeurIPS 2022 Structured Stochastic Gradient MCMC ICML 2022 Structured variational inference in Bayesian state-space models AISTATS 2022 Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks NeurIPS 2022 Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization CVPR 2022 Suppressing Static Visual Cues via Normalizing Flows for Self-Supervised Video Representation Learning AAAI 2022 Surrogate Likelihoods for Variational Annealed Importance Sampling ICML 2022 Symmetry-induced Disentanglement on Graphs NeurIPS 2022 TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels NeurIPS 2022 Total Variation Optimization Layers for Computer Vision CVPR 2022 Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems ICML 2022 Tractable Function-Space Variational Inference in Bayesian Neural Networks NeurIPS 2022 Transformers Can Do Bayesian Inference ICLR 2022 Uncertainty Modeling in Generative Compressed Sensing ICML 2022 Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression CVPR 2022 Unsupervised Image Representation Learning with Deep Latent Particles ICML 2022 Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE NeurIPS 2022 Unsupervised Opinion Summarisation in the Wasserstein Space EMNLP 2022 VACA: Designing Variational Graph Autoencoders for Causal Queries AAAI 2022