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Variational Inference

1946 directly classified papers

Papers per year

Papers

f-Divergence Variational Inference NIPS 2020
Flow Contrastive Estimation of Energy-Based Models CVPR 2020
Narrative Text Generation with a Latent Discrete Plan EMNLP 2020
A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model NIPS 2020
Streamlined Variational Inference with Higher Level Random Effects JMLR 2020
Trust-Region Variational Inference with Gaussian Mixture Models JMLR 2020
Variational Inference for Computational Imaging Inverse Problems JMLR 2020
Stochastic Talking Face Generation Using Latent Distribution Matching INTERSPEECH 2020
Exploring TTS Without T Using Biologically/Psychologically Motivated Neural Network Modules (ZeroSpeech 2020) INTERSPEECH 2020
Generalization Guarantees for Imitation Learning CORL 2020
Multi-Modal Anomaly Detection for Unstructured and Uncertain Environments CORL 2020
Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring CVPR 2020
PatchVAE: Learning Local Latent Codes for Recognition CVPR 2020
Bringing Old Photos Back to Life CVPR 2020
Improving Inference for Neural Image Compression NIPS 2020
Focus-Constrained Attention Mechanism for CVAE-based Response Generation EMNLP 2020
Inserting Information Bottlenecks for Attribution in Transformers EMNLP 2020
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space EMNLP 2020
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals MLHC 2020
An Empirical Investigation of Contextualized Number Prediction EMNLP 2020
Nonlinear System Identification via Tensor Completion AAAI 2020
IntroVNMT: An Introspective Model for Variational Neural Machine Translation AAAI 2020
Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020
Variational Neural Machine Translation with Normalizing Flows ACL 2020
Towards Visually Explaining Variational Autoencoders CVPR 2020