Variational Inference

Bayesian Attention Modules NeurIPS 2020 Bayesian Hierarchical Words Representation Learning ACL 2020 Bidirectional Convolutional Poisson Gamma Dynamical Systems NeurIPS 2020 Bi-level Score Matching for Learning Energy-based Latent Variable Models NeurIPS 2020 Black-Box Inference for Non-Linear Latent Force Models AISTATS 2020 Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics ICML 2020 Bootstrapping neural processes NeurIPS 2020 Bridged Variational Autoencoders for Joint Modeling of Images and Attributes WACV 2020 Bridging Maximum Likelihood and Adversarial Learning via α-Divergence AAAI 2020 Bringing Old Photos Back to Life CVPR 2020 Capsule Routing via Variational Bayes AAAI 2020 CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow ACML 2020 C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds CVPR 2020 CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models NeurIPS 2020 Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems ICML 2020 Complex-Valued Variational Autoencoder: A Novel Deep Generative Model for Direct Representation of Complex Spectra Interspeech 2020 Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding NeurIPS 2020 Conditional Gaussian Distribution Learning for Open Set Recognition CVPR 2020 Constraining Variational Inference with Geometric Jensen-Shannon Divergence NeurIPS 2020 Continual Learning with Adaptive Weights (CLAW) ICLR 2020 ControlVAE: Controllable Variational Autoencoder ICML 2020 Coping With Simulators That Don’t Always Return AISTATS 2020 Crossing Variational Autoencoders for Answer Retrieval ACL 2020 Data Uncertainty Learning in Face Recognition CVPR 2020 Deep Gaussian Markov Random Fields ICML 2020