Variational Inference

Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior AAAI 2020 Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation CVPR 2020 Learning Cross-Aligned Latent Embeddings for Zero-Shot Cross-Modal Retrieval AAAI 2020 Learning from Irregularly-Sampled Time Series: A Missing Data Perspective ICML 2020 Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE NeurIPS 2020 Learning Joint Articulatory-Acoustic Representations with Normalizing Flows Interspeech 2020 Learning Probabilistic Sentence Representations from Paraphrases ACL 2020 Learning Robot Skills with Temporal Variational Inference ICML 2020 Learning Sparse Prototypes for Text Generation NeurIPS 2020 Learning to Learn Kernels with Variational Random Features ICML 2020 Learning to Learn Variational Semantic Memory NeurIPS 2020 Learning VAE-LDA Models with Rounded Reparameterization Trick EMNLP 2020 Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers EMNLP 2020 Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders CVPR 2020 Lifted Hybrid Variational Inference IJCAI 2020 Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder NeurIPS 2020 Linear Disentangled Representations and Unsupervised Action Estimation NeurIPS 2020 Markovian Score Climbing: Variational Inference with KL(p||q) NeurIPS 2020 McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020 Meta-Amortized Variational Inference and Learning AAAI 2020 Meta-Learning with Shared Amortized Variational Inference ICML 2020 Mixed-curvature Variational Autoencoders ICLR 2020 MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space AAAI 2020 Model Fusion with Kullback-Leibler Divergence ICML 2020 Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows NeurIPS 2020