variational inference

Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory NeurIPS 2023 Few-Shot Object Detection via Variational Feature Aggregation AAAI 2023 Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation JMLR 2023 Flat Seeking Bayesian Neural Networks NeurIPS 2023 Free-Form Variational Inference for Gaussian Process State-Space Models ICML 2023 Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes ICML 2023 Function Space Bayesian Pseudocoreset for Bayesian Neural Networks NeurIPS 2023 Generalized Information-theoretic Multi-view Clustering NeurIPS 2023 Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting ICML 2023 Generative Label Enhancement with Gaussian Mixture and Partial Ranking AAAI 2023 Generative Modelling with Inverse Heat Dissipation ICLR 2023 Generative Semantic Segmentation CVPR 2023 Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables JMLR 2023 GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies NeurIPS 2023 GFlowNet-EM for Learning Compositional Latent Variable Models ICML 2023 GFlowNets and variational inference ICLR 2023 GFlowOut: Dropout with Generative Flow Networks ICML 2023 Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping AAAI 2023 Gradient-Free Kernel Stein Discrepancy NeurIPS 2023 Guiding Energy-based Models via Contrastive Latent Variables ICLR 2023 Harnessing Out-Of-Distribution Examples via Augmenting Content and Style ICLR 2023 Hierarchical VAEs provide a normative account of motion processing in the primate brain NeurIPS 2023 HierVST: Hierarchical Adaptive Zero-shot Voice Style Transfer Interspeech 2023 H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features ICML 2023 Identifiability Guarantees for Causal Disentanglement from Soft Interventions NeurIPS 2023