variational inference

A Variational Inference Approach to Learning Multivariate Wold Processes AISTATS 2021 A Variational Information Bottleneck Approach to Multi-Omics Data Integration AISTATS 2021 A Variational Information Bottleneck Based Method to Compress Sequential Networks for Human Action Recognition WACV 2021 A Variational Perspective on Diffusion-Based Generative Models and Score Matching NeurIPS 2021 BasisDeVAE: Interpretable Simultaneous Dimensionality Reduction and Feature-Level Clustering with Derivative-Based Variational Autoencoders ICML 2021 Bayesian Attention Belief Networks ICML 2021 Bayesian Context Aggregation for Neural Processes ICLR 2021 Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization AAAI 2021 Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression CVPR 2021 Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval ICCV 2021 BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery NeurIPS 2021 Behavior-Driven Synthesis of Human Dynamics CVPR 2021 Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech ICLR 2021 Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning AAAI 2021 Cascaded Head-colliding Attention ACL 2021 Categorical Normalizing Flows via Continuous Transformations ICLR 2021 Cluster-Wise Hierarchical Generative Model for Deep Amortized Clustering CVPR 2021 Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition ICML 2021 Collapsed Variational Bounds for Bayesian Neural Networks NeurIPS 2021 Composing Normalizing Flows for Inverse Problems ICML 2021 Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features NeurIPS 2021 Conditional Variational Capsule Network for Open Set Recognition ICCV 2021 Consistency Regularization for Variational Auto-Encoders NeurIPS 2021 Contextual Dropout: An Efficient Sample-Dependent Dropout Module ICLR 2021 Continuous Latent Process Flows NeurIPS 2021